{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": 53,
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "WARNING: replacing module FractionalFlow.\n"
     ]
    },
    {
     "data": {
      "text/plain": [
       "Main.FractionalFlow"
      ]
     },
     "execution_count": 53,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# load the package\n",
    "include(\"../FractionalFlow/FractionalFlow.jl\")\n",
    "using PyPlot, SetPyPlot, NLopt, Dierckx, BlackBoxOptim, Statistics\n",
    "import Calculus\n",
    "import GR\n",
    "FF = FractionalFlow"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Note\n",
    "For the tertiary low salinity water flooding, the recovery factor is calculated by \n",
    "$$R_{tert}=\\frac{S_{w,avg}-(1-S_{or,hs})}{S_{or,hs}}$$\n",
    "However, the recovery factor is usually reported as the percentage of the initial oil that is in the reservoir before the secondary formation water water flooding, i.e.,\n",
    "$$R=\\frac{S_{w,avg}-S_{w,init}}{1-S_{w,init}}$$\n",
    "To convert one to the other, we can write\n",
    "$$R=\\frac{\\left(R_{tert}S_{or,hs}+(1-S_{or,hs})\\right)-S_{w,init}}{1-S_{w,init}}$$\n",
    "We can also do it the other way around, i.e.,\n",
    "$$R_{tert}=\\frac{R\\left(1-S_{w,init}\\right)+S_{w,init}-\\left(1-S_{or,hs}\\right)}{S_{or,hs}}$$"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Tertiary Water-flooding"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 54,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": "iVBORw0KGgoAAAANSUhEUgAAAjcAAAGwCAYAAABVdURTAAAABHNCSVQICAgIfAhkiAAAAAlwSFlzAAAPYQAAD2EBqD+naQAAADh0RVh0U29mdHdhcmUAbWF0cGxvdGxpYiB2ZXJzaW9uMy4xLjEsIGh0dHA6Ly9tYXRwbG90bGliLm9yZy8QZhcZAAAgAElEQVR4nOzdd3hTZRvH8W+S7t3SQTdLlkARkD1VUER43QOU2QKCskQQQWWooCiCYgXKUBS3qKgoSxBkylZWGYVuuvdIk5z3jzCsrKbNKOX+XFcvTs/84SXtnec8Q6UoioIQQgghRA2htnUAIYQQQghzkuJGCCGEEDWKFDdCCCGEqFGkuBFCCCFEjSLFjRBCCCFqFCluhBBCCFGjSHEjhBBCiBrFztYBrM1gMJCcnIy7uzsqlcrWcYQQQghRAYqikJ+fT1BQEGr19dtmbrniJjk5mdDQUFvHEEIIIUQlJCQkEBISct1zbrnixt3dHTD+x/Hw8LBxGiGEEEJURF5eHqGhoZd+j1/PLVfcXHwV5eHhIcWNEEIIcZOpSJcS6VAshBBCiBpFihshhBBC1ChS3AghhBCiRpHiRgghhBA1ihQ3QgghhKhRpLgRQgghRI0ixY0QQgghahQpboQQQghRo0hxI4QQQoga5ZaboVgIIUQ1pdfDtm2QkgKBgdClC2g0tk4lbkI2bbnZunUrffv2JSgoCJVKxQ8//HDDa/744w9at26Nk5MT9erVY9GiRVZIKoQQwqJWr4Y6daBHD+jf3/hnnTrG/UKYyKbFTWFhIRERESxcuLBC58fFxXH//ffTpUsXDhw4wMsvv8yYMWP47rvvLJxUCCGExaxeDY8+ComJ5fcnJRn3S4EjTKRSFEWxdQgwLoT1/fff8+CDD17znMmTJ7NmzRqOHTt2ad/IkSM5dOgQO3furNBz8vLy8PT0JDc3VxbOFEIIG1N0OqhbFxITUQGlDg6oFAWHsjLjcZUKfVAwqQePVp9XVIoChjJUuhJUulJU+lKgWvwqrTbsHZ3xrR1m1nua8vv7pupzs3PnTnr16lVu37333suyZcsoKyvD3t7+imtKS0spLS299H1eXp7FcwohhIDc4jLiMgqJyyggLr2Q83mlZBRc/NKSXaSlxakDfHmhxUZrb098aCgKKsIT4nHUalEpCnZJiUwcs5BdYS0sntmZEuqqUqlz4StElUEtVZ7xi1xqqfJwowS1SoqZ6zlu1wTfabts9vybqrhJTU0lICCg3L6AgAB0Oh0ZGRkEBgZecc3s2bOZMWOGtSIKIcQtKS2vhIMJORxKzOFgQg7HU/LJLNTe8Dr/gmwAyjR2xIeEorOzx7G0BDudrtx5QcU5ONqZtyeFBwU0U52hOadprjrD7aozBKkyTb5PqWIv7Tb/oVfbtry4qYobML6++reLb9X+u/+iKVOmMGHChEvf5+XlERoaarmAQghxC8gtLmP7qQz+OJHOn6cySMopvup5AR6O1PV1pa6vK4Gezvi5O+Lr5oivmwM+rg547LZH98u7JISGUubggL1WS1hCAhqDodx95o3tzbzu3asWuqwYzm2H05vh9O+QdvTq5zl7g099qFUfvOuAmz+4+oOrH7j6gqMH2DuBnRNoHHC8xu+fW9ntNn7+TVXc1K5dm9TU1HL70tLSsLOzo1atWle9xtHREUdHR2vEE0KIGi0lt5g1B5PZeOw8++Nz0Bsut1eoVdAwwJ2IEC8iQr1oHuxJXT9X3Byv/2tG37k98fXqU6rRYFdWRlhCAnZ6/eUTVCoICTEOC6+Moiw4tgaO/ghnt4O+tPxx7zoQ1AqCWxn/9G8CLj6Ve5aoNm6q4qZDhw789NNP5fatX7+eNm3aXLW/jRBCiKrJKynjt79T+f5AErviMvn3EJT6fq50a+hPt0Z+tA73vmEh81+G0lISnx9DiUaDRq8jLCkRB13Z5RMutojMn29aZ+LSAjixFv7+Fk5vAsO/XnF5BEP9u4xfdbuB69U/GIubm02Lm4KCAk6dOnXp+7i4OA4ePIiPjw9hYWFMmTKFpKQkVq5cCRhHRi1cuJAJEyYQFRXFzp07WbZsGV988YWt/gpCCFEjHUvJY8X2OH44mIxWd/kVUdu6PvSNCKJ7Qz9CfVwqfX9FpyNpwgsU7d6N2tWV0EEDcZw7t/xw8JAQY2Hz8MMVu2nGSdgTAwc/B23+5f0BzaHZw9C4D/g2vFw0iRrLpsXN3r176dGjx6XvL/aNGTRoEB9//DEpKSnEx8dfOl63bl3Wrl3L+PHj+fDDDwkKCuL999/nkUcesXp2IYSoaQwGhc0n0lj2Zxw7Tl/uWHubvxsP3hHM/1oGEeJd+YLmIsVgIGXqVAo2bULl4EBIdDTO7drC6NGmz1BsMMDJdbB7MZzZfHm/Tz1o/hg0ewT8GlU5s7i5VJt5bqxF5rkRQojyFEXh139SmbchllNpBYCxD03vZoEM7VyHVmHe1xy0UZlnnX/9DbJXrQI7O0I+eB/3f33IrTCDAY79CFvegvSLc5+poFFvaBsFdbuDWpZPrElq7Dw3QgghzEdRFLadzGDuuhP8nZQLgLuTHU+1DWNgh3CztNL8V8YHHxgLG5WKoNmzTS9sDAY4/jNsmQNpR4z7HD2h9SC4c5ixg7C45UlxI4QQt6B/knJ5/Zej7DqTBYCrg4ZhXeoR2aUuHk6WGaCRueJjMqI/AqD2q6/g2fcB025wbif8NhlSDhm/d/SA9s9C+1Hg7GXmtOJmJsWNEELcQgpKdcxbH8vHO+IwKOCgUfN0+3BG9aiPr5vlps3I+e470t56CwC/8ePxfuqpil+clwIbXoW/vzZ+7+AO7UcaixoZti2uQoobIYS4Raw7ksr0NUdIyS0BoE+LQF6+vwnBXs4WfW7eb+tIeeVVAHyGDaXW8KiKXajTwq5o2DoXtAWACloNhLtfNU6mJ8Q1SHEjhBA1XEZBKVNW/82Go+cBCPVxZtb/mtG9kb/Fn12w7U+SXnwRDAa8HnsM/4kTK9Y5OfVv+H4knP/H+H3IndD7beNke0LcgBQ3QghRg22NTWfC14fIKCjFTq1ieNd6PH/XbTg7WH6F7aL9B0gcMwbKynDvfR+1p79248JGr4Pt7xlHQRnKwKUW9HodWjwpo59EhUlxI4QQNZBWZ2DuuuPEbIsDoGGAGwuevIMmgdaZAqPk+HESRoxAKS7GtWsXgt96C9WN5qxJP2FsrUneb/y+8QPwwHvGtZ2EMIEUN0IIUcPEZRTy/Bf7+ScpD4Bn2ocztU8TnOwt31oDoD17lvhhkRjy83Fu3ZqQBQtQOThc/6IDq+CXCaArMQ7tvn8utHhcZhMWlSLFjRBC1CDbTqYzetV+8kp0eLnY8/YjLeh1e22rPb8sJYVzQ4eiz8zEsWkTQhd9hNr5Oh2Wy0rg10mw/xPj9/Xvgn4LwTPYOoFFjSTFjRBC1ACKovDJjrPM+uUYeoNC63BvPuzfitqeTlbLoMvKIn7oMHTJKTjUqUNYTAwad/drX5B9Fr4eeGHeGhX0mApdXpC+NaLKpLgRQoibnFZn4LU1//DFngQAHm0dwhsPNcPRzjqvoQD0+fkkREahjYvDLjCQsOXLsKt1nRW3T22Eb4dBSQ44+8Cjy4ytNkKYgRQ3QghxE8stKmP4p3vZHZeFSgUv925CZJe6ZlsLqiIMxcUkPPssJUePovHxIWz5MuyDgq59wd7l8MtEUPQQ3AYe/wQ8Q6yWV9R8UtwIIcRNKj2/lGeW7eZ4aj7ujna8/9Qd9Ghs3ZFFilZL4rhxFO/dh9rdnbBlS3GsW9d4UK8vv8p3p06wZRZsX2A83nIAPDAf7G7Q2VgIE0lxI4QQN6HE7CKeWbaHuIxC/Nwd+XRYWxrXts4w74sUvZ7kl16i8I+tqJycCF28CKcmTYwHV6+GsWMhMfHyBbVc4G4Fmtgb+9d0fVFGQwmLkF5bQghxkzmdXsDji3YSl1FIiLcz347sYP3CRlFInTGTvLW/gr09IR+8j0urC7MHr14Njz5avrAByCyCr4vBIxK6TZLCRliMFDdCCHETOZKcy+OLdpKcW0IDfze+HdmR8FquVs+RPm8eOV9/DWo1wXPfxq1LF+MBvd7YYqMoAKR52ZHq869VxlXA/G+M5wlhIVLcCCHETeJEaj4Dlu4ms1BLs2APvhre3qpDvS/KWBJDZsxSAGrPmI7HffddPrht26UWmyRfewa9XI/ISXXI8LzQC0IBEhKM5wlhIVLcCCHETSAuo5ABS3eTU1RGy1AvPo9qTy03R6vnyP7yS9LnzQPAf9IkvB97rPwJKSkAnAtwYPCUuiT6O6BTqyixV131PCEsQToUCyFENZeUU8yAmF1kFJTSJNCDT4a0xcPJ/sYXmlnuz7+QOmMmALVGjqDW0CFXnhQYyMlgR6Im1SHT0546KaUsfSuOgBzdFecJYSlS3AghRDWWll/CgJhdJOeWUM/PlU+HtcXTxfqFTf6WLSS/9BIoCt79++M3duxVzzsSbmDklLrkuNnRML6Yxe+cxTfvX/1rVCoICYGLfXSEsAApboQQoprKKdLyzNI9nM0sIsTbmVWR7fC1wauowj17SBo7DnQ6PPr1JWDa1KtOEnjw3B88+8dYCtzsaHamiEXz4vEs+E9hAzB/PtxohXAhqkD63AghRDWk1RkY8ek+TpzPx9/dkVWR7Qj0vM4ClBZS/M8REp8dhVJailuPHgS98Qaqq6z9tPvcZoZvfo4CFbQqU4ipPw5Pr/8s2BkSAt9+Cw8/bKX04lYlLTdCCFHNKIrClNV/szsuCzdHO1YOa2uT4d6lp0+TEBmJobAQl7ZtCZ7/Hir7K1+JbT27gfFbJqBVQYdSPfP7folLYAsYMKr8DMVdukiLjbAKKW6EEKKaid5ymu/2J6JRq/hwQCurT9AHoE1MIn7oMPQ5OTg1b05IdDRqxytfia0/8yuTt01Cp4LuxWW802cljoEtjAc1Guje3brBhUBeSwkhRLXyy+EU5q47AcD0frfTraGf1TPo0tOJHzYU3fnzODSoT+iSxWjcrmw5+unUGl7cNgkdcF9RCfN6LcExtK3V8wrxX1LcCCFENXEgPpsJXx8EYGinujzTPtzqGfS5ucQPi6TsXDz2wcGELVuGnbf3Fed9feJrpm6figF4ML+QOT3mY1+vq9XzCnE18lpKCCGqgbS8EoZ/uo9SnYG7G/sztU8Tq2cwFBWRMGIkpbGxaPx8CVuxHPuAgCvOW3lkJXP3zgXgybx8ptz5EurGfawdV4hrkuJGCCFsrExv4LnPD5CeX0qjAHfef+oONGrrLipp0GpJfO55ig8eRO3pSdiyZTiEhZU7R1EUlhxewsKDCwEYkpPH+AaPoWo/0qpZhbgRKW6EEMLG5q47wZ6zxpFRHz3dCldH6/5oVnQ6kl+YSOGOHahcXAhbshinhg3Ln6MoLNi/gGX/LANgdHYOI3zbobpvjlWzClERUtwIIYQN/fZPCku2ngHgncdaUM/PzarPVwwGUl59jfwNG1DZ2xP64UKcIyLKnWNQDLy15y0+P/45ABMzsxnkHA6PrQCN/BoR1Y/8XymEEDZyJr2Aid8cBiCqS13ua2bd9ZYURSHtrbfIXb0aNBqC35uHa4cO5c7RG/TM2DmD7099D8ArGVk8bnCB/l+Bo7tV8wpRUVLcCCGEDRRr9YxatZ+CUh131vFm0n2NrZ4hIzqarE9WAhD4xuu433NPueNlhjKm/jmVX+N+RY2KWekZ9CsqhUHfgGeI1fMKUVFS3AghhA3M/PkIx1Pz8XVzZGH/VthrrDszR9bKT8n4wNgxOODll/F68MFyx7V6LRP/mMjmhM3YqdTMScvg3oJCuG8OhHe0alYhTCXFjRBCWNn6I6l8sScBlQoWPNmSAA8nqz4/54cfOP/mmwD4Pv8cPgOfKXe8WFfMuM3j2JG8Awe1PfOyCulWUADNHoV2MjJKVH9S3AghhBWl5Zfw0uq/AYjqUo9ODXyt+vz8jRtJmToNAJ9BA/EdNarc8cKyQkZvGs2+8/tw1jjxvtaF9tmnwb8p9Hv/8sreQlRjMkOxEEJYiaIoTPr2MFmFWhrXdueFXg1vfJEZFe7cSdL4CaDX4/nww/hPnozqX8VKbmkuUeuj2Hd+H272biz2bE37+IPg6AFPfAYO1l+8U4jKkOJGCCGs5NNd59hyIh0HOzXvP3UHjnbWWyG7+NAhEkY/h1JWhnvPngTOnIFKfflXQGZxJsPWDePvjL/xdPRkaZMo7tj3hfHggx9BrfpWyypEVclrKSGEsIJTafm88csxAKb0bkzDAOsNoy45EUv88BEoRUW4duxI0LvvoLK7/OP/fOF5ojZEEZcbRy2nWizpNJuGnz9tPNh2ODR5wGpZhTAHabkRQggLK9MbGPfVQUp1Brrc5sugDnWs9mxtfDzxkcMw5Obi3LIlIQs/QO3gcOl4UkESg38bTFxuHAEuAXx873Ia/v4WFGWA/+3Qc5bVsgphLlLcCCGEhS3ZeoZ/kvLwcrHnncciUFtp3aiy8+eJHzoMfXoGjo0aEbp4EWoXl0vHz+aeZdCvg0gsSCTELYRPen9CnSM/wZnNYOcMjy4He+uO5BLCHKS4EUIICzqVVsCCTScBeK1vU6sN+9ZlZxM/bBhliYnYh4cRtjQGjafnpeMns08y+LfBnC86T13Punx838cE56bCppnGE3rPAX/rTywohDlIcSOEEBZiMChMWX0Yrc5A90Z+PNgy2CrP1RcUkjB8BNpTp7ELCCBs2XLs/PwuHT+SeYQh64aQWZJJI+9GrLh3BQF2rvDtMDDooOmD0GqQVbIKYQnSoVgIISxk1e5z/HU2G1cHDa8/2KzcsGtLMZSUkDhqFCV//43G25uw5ctwCLlcVB1IO8CojaMoKCuguW9zPrrnIzwdPeHnCZAdBx4h0HeBzGcjbmrSciOEEBaQlFPMnF+PAzC5d2NCvF1ucEXVKWVlJI2fQNGePahdXQmNicGx/uUh3LtSdjFiwwgKygpoHdCaJT2XGAub05th7zLjSQ9+CM5eFs8qhCVJcSOEEGamKApTv/+bQq2eNuHePN0u3PLPNBhInjqVgs2bUTk6EvJRNM7Nbr90fGviVkZvHE2xrpiOQR356J6PcHNwg5Jc+PE540l3RkG97hbPKoSlSXEjhBBmtuZQsnGyPo2aOY+0sPjoKEVROP/6G+St+Qns7AheMB/Xtm0vHV93dh1jfx+L1qClR2gPPrjrA5ztnI0Hf3sZ8hLBuy70nGHRnEJYixQ3QghhRnklZcz62ThZ35i7G9DA383iz0xfsIDszz8HlYqgOXNw79790rE1p9cwaeskdIqO3nV68273d3HQXJjn5sRvcPAzQGWchViWVxA1hHQoFkIIM5q/4SQZBaXU83NleFfLL1mQuXwFmYsWA1D7tVfxfKDPpWNfn/iaWbuMk/A91OAhXuvwGhr1hSUfirLgpzHG7Q6jIbyDxbMKYS1S3AghhJkcT83jk51nAZjR73Yc7CzbOJ79zTekvf02AH4TJuD95JOXjn1y5BPe2fsOAP0b92dy28moVf/K89tLUHAefBvCXdMsmlMIa5PiRgghzEBRFF794Qh6g0LvZrXpcpvfjS+qgrzffiP11dcAqBU5DN/hUZdyLDq8iOiD0QAMazaMsa3Glh+GfmoTHP6KS6+j7J0tmlUIa5PiRgghzOCHg0nsOZuFs72GaQ80teizCrZtI+nFSaAoeD3+OH4vvAAYC5v39r/Hin9WAPBcy+cY3mJ4+cJGWwg/jzdutxsBIW0smlUIW5DiRgghqiivpIw31xrntHnurgYEe1muJaRo3z4Snx8DZWV43N+b2q+9ikqlwqAYmLNnDl8c/wKAF9u8yMDbB155gy1zIOeccbI+eR0laigpboQQoormbzhJen4pdX1diexS12LPKTl2jISRz6KUlODatQtBc+ag0mjQG/RM3zmdH079gAoV09pP4/FGj195g5RDsPND43afd8HR3WJZhbAlKW6EEKIKTp7Pv9SJeHq/23G001jkOaVxccQPi8SQn49zm9aELFiAysGBMkMZL297md/O/oZapeb1Tq/Tt37fK2+g18GaMaDo4faHoNF9FskpRHUgxY0QQlTBm2uPoTco9GwaQLeGlulEXJacTPzQYeizsnBq2pTQjz5C7exMqb6UiX9MZEvCFuzUdrzd9W16hve8+k12L4KUg+DkCfe9ZZGcQlQXUtwIIUQl/Xkyg80n0rFTq5jSu7FFnqHLzCR+6DB0KSk41K1L6NIYNO7uFOuKGfv7WHam7MRB7cB7Pd6ja0jXq98kJwE2v2Hc7jkL3AMsklWI6kKKGyGEqAS9QeH1X44C8HT7cOr5mX8mYn1+PvFRUWjPnsUuKJCw5cuw8/GhQFvA6E2j2Z+2H2c7Zz646wPaBba79o3WTYGyIgjrCHc8Y/acQlQ3Nl9+ITo6mrp16+Lk5ETr1q3Ztm3bdc+fP38+jRo1wtnZmdDQUMaPH09JSYmV0gohhNF3+xM5npqPu5MdY+6+zez3NxQXkzDyWUqPHkNTqxbhy5djHxhIbmkuUeuj2J+2Hzd7N5b0XHL9wubURjj2E6g00OcdUNv8x74QFmfTlpuvvvqKcePGER0dTadOnVi8eDG9e/fm6NGjhIWFXXH+qlWreOmll1i+fDkdO3YkNjaWwYMHA/Dee+9ZOb0Q4lZVpNXxzroTADx/VwN8XB3Men9FqyVxzFiK9+1D7e5O2LKlONSpQ2ZxJsM3DCc2OxYvRy8W91xM01rXmVNHVwprJxm3242AgNuvfa4QNYhNS/h58+YxbNgwIiMjadKkCfPnzyc0NJSPPvroqufv3LmTTp060b9/f+rUqUOvXr146qmn2Lt37zWfUVpaSl5eXrkvIYSoiiVbz5CWX0qojzODOtYx670VvZ6kyZMp3LYNlbMzoYsX4dS4MecLzzP4t8HEZsdSy6kWy+9dfv3CBmDnQsg6DW4B0P0ls+YUojqzWXGj1WrZt28fvXr1Kre/V69e7Nix46rXdO7cmX379rFnzx4Azpw5w9q1a+nTp89VzweYPXs2np6el75CQ0PN95cQQtxyzueVsPiPMwBMvq+xWYd+K4pC6vTp5P/6G9jbE/L++7i0akVifiKDfhvE2byz1HatzSe9P+E27xu8CstJgK3GtaXoOcs4SkqIW4TNXktlZGSg1+sJCCjfaz8gIIDU1NSrXvPkk0+Snp5O586dURQFnU7Hs88+y0svXfsTyZQpU5gwYcKl7/Py8qTAEUJU2nsbYiku03NHmBd9mgea7b6KopD2zjvkfPMtqNUEz52LW5fOxOXGEbk+krSiNELdQ1naaylBbkE3vuG6ly93Im5xlQn9hKjBbD5aqtyaJxj/gf9330VbtmzhjTfeIDo6mnbt2nHq1CnGjh1LYGAgr7zyylWvcXR0xNHR0ey5hRC3ntPpBXyzLxGAqfc3uebPqsrIXBJD1rLlAATOmonHffdyIusEwzcMJ6ski3qe9YjpFYO/i/+Nb3ZqExxbc7kTsRlzCnEzsFlx4+vri0ajuaKVJi0t7YrWnIteeeUVnnnmGSIjIwFo3rw5hYWFDB8+nKlTp6KWUQBCCAt6b0MseoPC3Y39aVPHx2z3zf7iC9IvDIrwnzwZr0ce4Z+MfxixYQR52jwa+zRmcc/F+DhV4Jn6MvjtQmu2dCIWtyibVQMODg60bt2aDRs2lNu/YcMGOnbseNVrioqKrihgNBoNiqKgKIrFsgohxJHkXH4+nALAC70ame2+uT/9TOrMWQDUenYktYYMZv/5/USujyRPm0cL3xYs7bW0YoUNwN4VkBELLrWg22Sz5RTiZmLT11ITJkzgmWeeoU2bNnTo0IElS5YQHx/PyJEjARg4cCDBwcHMnj0bgL59+zJv3jzuuOOOS6+lXnnlFfr164dGY5n1XIQQArg09LtfRBBNgzzMcs/83zeT/NJLoCh4DxiA35gx7EzeydjNYynWFdMmoA0L716Iq71rxW5YlAVb3jRu3zUNnL3MklOIm41Ni5snnniCzMxMZs6cSUpKCs2aNWPt2rWEh4cDEB8fX66lZtq0aahUKqZNm0ZSUhJ+fn707duXN954w1Z/BSHELeCvs1lsPpGORq1ifM+GZrln4e49JI0bB3o9nv/rR8DUl/kj8Q9e2PICWoOWTkGdeK/HezjbOVf8pn+8DcXZ4N8U7hholpxC3IxUyi32PicvLw9PT09yc3Px8DDPpy8hRM2lKApPLN7FnrNZPNU2lNkPt6jyPYv//of4QYMwFBXhdtddhCyYz7qkTUzZOgWdouOu0LuY220uDhoTJgfMOAnR7cGgg2e+h/p3VTmnENWJKb+/pQeuEEJcx9aTGew5m4WDnZrn76r6Mgulp06REBWFoagIl3btCH5vHmvOrWXy1snoFB33172fd7q/Y1phA7B+mrGwadhbChtxy7P5UHAhhKiuFEVh7rrjADzTPpwgLxNeEV2FNjGR+KHD0Ofk4NSiBSEffsjXcd/zxm7jq/VHbnuEV9q/gkZtYh/CU5sg9jdQ20Gv16uUUYiaQIobIYS4hnVHzvNPUh6uDhpGda9fpXuVpaURP3QYurQ0HG9rQOjiRXx69hve3fcuAAOaDGDynZNNnztHr4N1U43bbYeDb4Mq5RSiJpDiRgghrkJRFN7fdBKAwZ3qUMut8pOB6nNySBgWSVl8PPYhIYQsXUrMuS+JPhQNQGTzSMbcMaZykwIe/AzSj4GzN3SbVOmMQtQkUtwIIcRVbDyWxtEUY6tNZOd6lb6PobCQ+BEjKD15Ejs/P0KXL2NhwipWHFkBwJg7xhDVIqpyN9cWwuYLQ7+7TTYWOEIIKW6EEOK/FEVhwaZYAAZ2rIO3q4mdey8waLUkPPccJYcOo/b0JGRpDHOTV/LVia8AmHTnJJ5p+kzlg+6MhoLz4BUObYZW/j5C1DBS3AghxH/8fjyNf5LycHHQENWlcq02ik5H8gsvULRzF2oXF4IXL+KN9E/58fSPqFDxSodXeKzhY5UPWZgB2xcYt+9+FexkDT0hLpLiRggh/uXffW2eaR+OTyVabRSDgZRpr5C/YSMqBwdqL1zA9NzPWHd2HTpMDKIAACAASURBVBqVhlmdZtG3ft+qBf3jbdDmQ2BLuP3hqt1LiBpGihshhPiXLbHpHErMxdleQ1RX01ttFEXh/Jw55P7wA2g0+L/7FtOKv2JL4hbs1HbM7TqXe8LvqVrIrDOw17iCOD1ngiwaLEQ5UtwIIcQFiqKwYKOx1ebp9mH4VmKEVMaH0WSv/BSAWrNeY7LyHbsSd+GocWRe93l0Dela9aCbZoGhDBrcA/W6Vf1+QtQwUtwIIcQFW09mcDAhByd7NcO7mj6vTdbKlWQsXAiA15QXedH5Z/an7MfZzpmFdy2kbWDbqodM2gdHVgMquGdG1e8nRA0kxY0QQmBstfngQl+bAe3C8XM3rdUmZ/X3nH9zNgDuo4YzvtZ6jqQdwd3eneh7omnp39IcIWHDa8btiCehdrOq31OIGkiKGyGEAP46m83ec9k4aNSMMLGvTd769aRMmwaA89NPMCZ8KyczT+Hl6MXinotpWqupeUKe2QJnt4HGAXpMNc89haiBpLgRQgggesspAB5tE4K/h1OFryvcsYPkFyaCwYDD/3rzfNO9nM05h6+zLzE9Y2jgbablEBQFfp9l3G4zDLxCzXNfIWqgChU377//vsk3HjJkCO7u7iZfJ4QQ1nY0OY8tJ9JRqzCp1ab44EESnnsepawMzV2dea7NERLzkwl0DWRpr6WEeYSZL+SJtcb+Nvau0GWC+e4rRA1UoeJm3LhxhISEoNFUbKXahIQEHnjgASluhBA3hY/+OA1AnxZBhNdyrdA1JSdOED98BEpREap2rXi+y2mSi9IJdQ9laa+lBLkFmS+gQQ+/X1jtu/1IcPM3372FqIEq/Fpq7969+PtX7B+UFDVCiJvFucxCfjmcDMDIbhVrtdGeO0f8sEgMeXnQvDHP35NAqjab+p71iekVg5+Ln3lD/vMdpB0FJ0/o+Lx57y1EDVSh4ua1117Dzc2twjd9+eWX8fHxqXQoIYSwlsVbz2BQoHsjP24P8rzh+WXnzxM/ZCj6jAyU+uGM7Z1KqqGAJj5NWNRzET5OZv7Zpy+7vDhmp7GyOKYQFVDh4sYUU6ZMqVQYIYSwprS8Er7dmwjAqO437viry84mfugwypKTMQQHMP5/WaRqionwiyD6nmg8HDzMH/LAZ5AdB65+0G6k+e8vRA1UpTm758yZQ05OjrmyCCGEVS3bHodWb6B1uDd31rl+i4i+oICEyCi0p09j8PPmhYfySXEs5s7ad7Kk5xLLFDZlxcY1pAC6TASHivUHEuJWV6Xi5s033yQrK8tcWYQQwmpyi8tYtSsegFHd66NSqa55rqGkhMRnR1Fy5AgGTzcmPVxEkruWzsGdib47Ghd7F8uE3LsC8pPBIwTaDLHMM4SogapU3CiKYq4cQghhVat2n6OgVEejAHd6NLr2YAmlrIykceMp+usvDC5OTHtES7yPnnvC7mFBjwU42VV8ThyTaIvgz/eM291eBDvT17kS4lYlS8kKIW45Wp2Bj7efBWB413qo1VdvtVEMBpKnvEzBli0YHOyY+bCOUwEG+tTrw9xuc3HQOFgu5N5lUJgGXuHQcoDlniNEDVSlGYqPHj1KUJAZ53IQQggrWHMombT8UgI8HOkbcfWfYYqikDprFnk//4yiUfPW/wwcDVXzyG2P8Er7V9CoKzbvV6VoC+HP+cbtri+Cxt5yzxKiBqpScRMaKtN/CyFuLoqisHTbGQAGd6yLg93VG7DT5y8g54svUVSw4AE40EDN002eZtKdk67bP8cs/loKRRngXce4QKYQwiQVei3l4+NDRkZGhW8aFhbGuXPnKh1KCCEsZdvJDI6n5uPioKF/26svj5C5bBmZixcDsOReNTuaqolqHmWdwqa0ALYvMG53nSStNkJUQoVabnJycvj111/x9LzxBFcAmZmZ6PX6KgUTQghLiLnQavPEnaF4ulxZOGR//TVpc98BYFV3NZvuUDO21Vgim0daJ+CeJVCUCT71oMUT1nmmEDVMhV9LDRo0yJI5hBDC4o6l5LHtZAZqFQztVPeK43lr15L62nQAvu+g4scOaibfOZmnmz5tnYCl+bDjwkLFXSeBpko9B4S4ZVXoX47BYLB0DiGEsLil2+IA6N08kFCf8nPTFGzdStKkyaAorL9DxZfdNEzvMJ1HGj5ivYC7F0NxNvjUh+aPWe+5QtQw8rFACHFLOJ9XwppDSQBEdSm/QGbR3r0kjhkLOh3bm6j4+F57Znd9kz71+lgvYGk+7Fxo3O42WVpthKgC+dcjhLglfLzjLGV6hbZ1fGgZ6nVpf/GRI8SPfBalpIR99VUs+p8D7/R4l7vD77ZuwD0xxlabWg2g+aPWfbYQNYwUN0KIGq9Iq2PVLuMIzsgul/valJ6JIz4qCqWggKOh8OGjzszvuYDOwZ2tG1BbeLnVpstEsOQcOkLcAqS4EULUeN/tTyKvREd4LRfuaRIAQFlyMueGDsGQlc2Z2vD+U+683/tD7qx9p/UD7l1uHCHlXUf62ghhBlLcCCFqNINBYcV2Y0fiwR3roFar0GVkEDd4MPrU8yTWggVPe/J+38VE+EVYP2BZMWy/MEKqywvS10YIMzB5bakBAwawZMkSYmNjLZFHCCHMauvJdM6kF+LuaMdjbULR5+VxZugQ9PEJpHnCBwN9WPDQCtsUNgD7PjGuIeUZBi1kNmIhzMHk4sbNzY158+bRuHFjgoKCeOqpp1i0aBHHjx+3RD4hhKiSFRcWyHysTSguei2no4ahjz1FjitED/bjvSdW0qRWE9uEKyuB7RfWkOo8DuwsuBCnELcQk4ubxYsXc/z4cZKTk5k3bx6enp4sWLCA22+/ncDAQEtkFEKISjmVVsAfsemoVDDozmBOjRqB/tA/FDjB4iEBzB3wGfW96tsu4MHPID8F3IPgDitNFCjELaDSL3fd3d3x9vbG29sbLy8v7OzsqF27tjmzCSFElXy8w9jXpmcjP0pmTcSway8l9rBicBCzB39GoJsNP5DptJdX/u48DuwcbZdFiBrG5JabyZMn0759e3x9fZk2bRparZYpU6Zw/vx5Dhw4YImMQghhstyiMr7blwSKwqDdSzFs+hOdGj4fGMqM4V/atrABOPQF5CaAWwC0GmjbLELUMCa33MydOxc/Pz9ee+01/ve//9GkiY3eVQshxNXo9bBtG3/9fpCIU0V0NhzH59BfGFTw7YAwXn7+S7ydvG2cUQd/vmfc7jgG7J1tm0eIGsbk4ubAgQP88ccfbNmyhXfffReNRkO3bt3o3r073bt3l2JHCGE7q1fD2LGQmMg9QEufWqT7+QHwyxPhvPDi13g4eNg2I8DRHyA7Dpx9oM0QW6cRosYxubiJiIggIiKCMWPGAHDo0CHmz5/PmDFjMBgM6PV6s4cUQogbWr0aHn0UFAWALC+vS4WNf9p5xjZ9FcfqUNgYDLDtXeN2+1Hg4GrbPELUQJXqUHzgwAG2bNnCli1b2LZtG3l5ebRs2ZIePXqYO58QQtyYXm9ssblQ2OR6eHA+wDjAwTcjA5+cHFQTJ8Mjj4PGxksbxP4KaUfBwR3aRto2ixA1lMnFjbe3NwUFBURERNC9e3eioqLo2rUrHh7V4BOREOLWtG0bJCYCkO/qSnJtY2dh7+wsfDMzUAEkJBjP697dZjFRlMutNm0jwdnGfX+EqKFMLm4+/fRTKWaEENVLSsqlTfuyMuz0OlwLiwhISzMWNlc5zybObIGkfWDnBO1H2zaLEDWYycXNAw88cGk7MTERlUpFcHCwWUMJIYRJ/jWBqJNWS51z57DT6coXNv85zyYuttq0GgRufrbNIkQNZvI8NwaDgZkzZ+Lp6Ul4eDhhYWF4eXkxa9YsDAaDJTIKIcR1Lfc6Saq3HRd/Atn/t7BRqSA0FLp0sUG6C+J3w9ltoLaHTmNsl0OIW4DJLTdTp05l2bJlzJkzh06dOqEoCtu3b2f69OmUlJTwxhtvWCKnEEJcQVEUPjz4IYsPL+bwgEDeW5iAgf98alNdKHPmz7dtZ+KLrTYRT4JniO1yCHELUCnKheEFFRQUFMSiRYvo169fuf0//vgjo0aNIikpyawBzS0vLw9PT09yc3Ol35AQNzFFUXhn7zusPLoSgL6hkWR+kMaM35dQOy/j8omhocbC5uGHbZQUSP0bFnUGlRqe2wu1bLielRA3KVN+f5vccpOVlUXjxo2v2N+4cWOysrJMvZ0QQpjMoBh4fdfrfBP7DQAvtX2JjbtuY3OjdEIHP8k0z0xj5+HAQOOrKFsP/764hlTTB6WwEcIKTO5zExERwcKFC6/Yv3DhQiIiIswSSgghrkVn0DHtz2l8E/sNKlTM7DiTTn4PsiU2HYCnO9UzDvd+6injn7YubLLOwJHVxu3O42ybRYhbhMktN2+//TZ9+vRh48aNdOjQAZVKxY4dO0hISGDt2rWWyCiEEACU6cuYvG0yG85tQKPS8GbnN7m/3v28/vNRFAW6N/Kjjm81m/F3xwegGKDBPRAoHwCFsAaTW266detGbGwsDz30EDk5OWRlZfHwww9z4sQJuthyJIIQokYr0ZUwdvNYNpzbgL3annnd53F/vfsp1ur5em8CAIM61LFtyP/KPw8HVhm3O0+wbRYhbiGVWn4hKChIRkUJIaymqKyIMb+PYXfqbhw1jizosYBOwZ0AWHMoibwSHWE+LnRrWM3mjtkVDfpSCGkL4R1tnUaIW0aFipvDhw9X+IYtWrSodBghhPivfG0+ozaO4mD6QVzsXFh490LurH0nYBwxtXLnOQCebh+GWn3FtH22U5wDfy0zbneZcHlIuhDC4ipU3LRs2RKVSsWNRo2rVCpZFVwIYTbZJdmM2DCCY1nHcHdwZ9E9i2jhd/kD1MGEHI4k5+Fgp+ax1qE2THoVe5eBNh/8msBt99o6jRC3lAr1uYmLi+PMmTPExcVd9+vMmTMmB4iOjqZu3bo4OTnRunVrtm3bdt3zc3JyGD16NIGBgTg5OdGkSRPpyCxEDZRRnMHQdUM5lnUMHycfVty7olxhA/DpLmOrzQMtAvF2dbBFzKsrK4ZdHxm3O48HtcndG4UQVVChlpuHHnqITZs24e3tzcyZM5k4cSIuLi5VfvhXX33FuHHjiI6OplOnTixevJjevXtz9OhRwsLCrjhfq9XSs2dP/P39+fbbbwkJCSEhIQF3d/cqZxFCVB+phalEro/kXN45/J39iekVQz2veuXOyS7U8vNh40KYz7QPt0XMazvwGRSmg2cYNLPh5IFC3KIqNEOxs7MzJ0+eJCQkBI1GQ0pKCv7+/lV+eLt27WjVqhUfffTRpX1NmjThwQcfZPbs2Vecv2jRIubOncvx48ext7ev0DNKS0spLS299H1eXh6hoaEyQ7EQ1VRCXgKR6yNJLkwmyDWIpb2WEupx5SunJVtP8+ba4zQL9uCn5zqjqi59WvQ6+OAOyImH3nOh3XBbJxKiRjD7DMUtW7ZkyJAhdO7c2Tjl+Tvv4ObmdtVzX3311QqF1Gq17Nu3j5deeqnc/l69erFjx46rXrNmzRo6dOjA6NGj+fHHH/Hz86N///5MnjwZzTUm6po9ezYzZsyoUCYhhG2dzjlN1Poo0ovTCfcIZ2mvpdR2rX3FeQaDwme74gF4ul149SlsAI7+YCxsXGrBHU/bOo0Qt6QKFTcff/wxr732Gj///DMqlYpff/0VO7srL1WpVBUubjIyMtDr9QQEBJTbHxAQQGpq6lWvOXPmDL///jsDBgxg7dq1nDx5ktGjR6PT6a753ClTpjBhwuX5JS623AghqpfjWccZvn442aXZNPBqQEyvGHydfa967taT6cRnFeHuZEe/lkFWTnodinJ5qYV2I8Gh6q/vhRCmq1Bx06hRI7788ksA1Go1mzZtMstrKeCKT1yKolzzU5jBYMDf358lS5ag0Who3bo1ycnJzJ0795rFjaOjI46OjmbJKoSwjMPphxm5cST52nya1mrK4nsW4+Xkdc3zL7baPNo6BBeHSk3XZRmnN8H5v8HeFe6MtHUaIW5ZJv9UMBgMZnmwr68vGo3milaatLS0K1pzLgoMDMTe3r7cK6gmTZqQmpqKVqvFwaEajZYQQlTIX6l/8dym5yjSFdHSryXR90Tj7nDtQQKJ2UX8fvw8AAPaVbOOxBdbbVoPAhcf22YR4hZms/GJDg4OtG7dmg0bNpTbv2HDBjp2vPpMnp06deLUqVPlCqzY2FgCAwOlsBHiJrQ9aTvPbnyWIl0R7Wq3Y3HPxdctbAC+2BOPQYGO9WvRwP/qff9sInEfnN0GajvoMNrWaYS4pdl08oUJEyawdOlSli9fzrFjxxg/fjzx8fGMHDkSgIEDBzJlypRL5z/77LNkZmYyduxYYmNj+eWXX3jzzTcZPVp+kAhxs9kUv4nnf3+eUn0pXUO6svDuhbjYX7+PilZn4Ku/EgF4uroN/97+nvHP5o+DZ4htswhxi7Ppy+onnniCzMxMZs6cSUpKCs2aNWPt2rWEhxt/aMXHx6P+1+RXoaGhrF+/nvHjx9OiRQuCg4MZO3YskydPttVfQQhRCWvPrOXlP19Gr+jpGd6Tt7q8hb3mxtM7bDh6noyCUvzcHenZ9Oqvr20i4yQc+9m43WmsbbMIISo2z01NYso4eSGE+a0+uZrpO6ajoNCvfj9mdJyBnbpin7P6x+xix+lMnr+rAS/0amThpCb48Tk48Ck07A39v7R1GiFqJLPPcyOEEOaw6tgq5uyZA8DjDR9navupqFUVezt+Or2AHaczUavgybZXzmBuM3kpcPgr43bncbbNIoQAKljceHt7V3iSrKysrCoFEkLUTEv/XsqC/QsAGNh0IBPbTDRp8r0vdhuHf/do5E+wl7NFMlbK7o9Ar4XQ9hDW3tZphBBUsLiZP3++pXMIIWooRVH44MAHxPwdA8DIiJGMihhlUmFTUqbn2/3GjsQD2lejVpuSXNi7wrgtrTZCVBsVKm4GDRpk6RxCiBpIURTe/uttPjv2GQDjW49naLOhJt9n7d8p5BSVEezlTLeG5plA1Cz2fQyleeDXGG6719ZphBAXVKnPTXFxMWVlZeX2SSddIQSAQTEwa9csvo39FoApbafQv0n/St1r1YVXUv3bhaFRV5N1pHSlsDPauN1xDKhtOrOGEOJfTP7XWFhYyHPPPYe/vz9ubm54e3uX+xJCCJ1Bx9Q/p/Jt7LeoVWpmdpxZ6cLmWEoe+85lY6dW8VibajR/zOGvoSAV3AOh+WO2TiOE+BeTi5tJkybx+++/Ex0djaOjI0uXLmXGjBkEBQWxcuVKS2QUQtxEyvRlTNo6iZ/P/Iydyo63urzFQ7c9VOn7rdp9DoB7b6+Nv7uTuWJWjcEAO943brcfBXYyQ7oQ1YnJr6V++uknVq5cSffu3Rk6dChdunShQYMGhIeHs2rVKgYMGGCJnEKIm0CJroQJWyawLWkb9mp73u32Lj3CelT6foWlOn44kAzAgHbVqCNx7K+QEQuOntB6sK3TCCH+w+SWm6ysLOrWrQsY+9dcHPrduXNntm7dat50QoibRlFZEaM3jWZb0jacNE4svGthlQobgDWHkiko1VHX15UO9WuZKakZbDcOaefOoeAk/QyFqG5MLm7q1avH2bNnAWjatClff/01YGzR8fLyMms4IcTNIU+bx/ANw9mTugdXe1cW9VxEx+CrL4BriouvpPq3DTNp6LhFxe+ChN2gcYB2I22dRghxFSYXN0OGDOHQoUMATJky5VLfm/Hjx/Piiy+aPaAQonrLLskmcl0kh9IP4e7gTkzPGFoHtK7yfQ8n5vBPUh4OGjWPtK5GHYn/vDDvV8RT4F7btlmEEFdlcp+b8ePHX9ru0aMHx48fZ+/evdSvX5+IiAizhhNCVG/pRekM3zCcUzmn8HHyYUnPJTTyMc+aT59fGP7du3ltfFyrSYfdtOPG/jaooOPztk4jhLiGKq8tFRYWRlhYNeroJ4SwipSCFCLXRxKfH4+/sz8x98ZQz7OeWe6dX1LGmkPGjsT9q9M6Ujs+MP7ZuA/43mbbLEKIa6pUcbNp0yY2bdpEWloaBoOh3LHly5ebJZgQovqKz4sncn0kKYUpBLsFE9MrhlD3ULPd/4eDyRRp9TTwd6NtXR+z3bdK8pL/tUDm+OufK4SwKZOLmxkzZjBz5kzatGlDYGBg9enkJ4SwitM5p4laH0V6cTp1POoQ0yuG2q7m63uiKMqlV1JPVaeOxLs+AkMZhHeCkDa2TiOEuA6Ti5tFixbx8ccf88wzz1gijxCiGjuWeYwRG0aQXZpNA68GxPSKwdfZ16zPOJCQw7GUPBzs1DzSKtis96604pzLC2R2GmvbLEKIGzJ5tJRWq6Vjx6oP8RRC3FwOpR9i2LphZJdmc3ut21lx7wqzFzZwuSPxAy0C8XKpJh2J960AbT74NYEGPW2dRghxAyYXN5GRkXz++eeWyCKEqKb+Sv2L4euHk1+Wzx3+dxDTKwYvJ/PPa5VbXMbPh6vZjMS6UuMrKYBOskCmEDcDk19LlZSUsGTJEjZu3EiLFi2wt7cvd3zevHlmCyeEsL0/k/5k3OZxlOpLaR/YngU9FuBi72KRZ32/P5GSMgONAtxpFVZNFuI9/BUUnAePYGj2qK3TCCEqwOTi5vDhw7Rs2RKAf/75p9yxatPxTwhhFpvObWLi1onoDDq6hXTj3e7v4qhxtMizFEXh8z3GV1L921WTjsQGA2yXBTKFuNmYXNxs3rzZEjmEENXML2d+YeqfU9Ereu6tcy+zu8zGXm1/4wsrad+5bGLPF+Bkr+bBO6pJR+ITayHz5IUFMgfZOo0QooKq9PI4MTGRpKQkc2URQlQT38V+x5RtU9ArevrV78dbXd6yaGEDlzsS920RhKezZZ9VIYoC2y8stXDnMHB0t20eIUSFmVzcGAwGZs6ciaenJ+Hh4YSFheHl5cWsWbOumNBPCHHz+ezoZ0zfOR0FhScaPcGsTrPQqDUWfWZOkZaf/04BjK+kqoX4nZD4F2gcof2ztk4jhDCBya+lpk6dyrJly5gzZw6dOnVCURS2b9/O9OnTKSkp4Y033rBETiGEFcQcjuH9A8Y+JoNvH8yE1hOs0vflu/1JaHUGmgR60DLU/KOwKuXiApkt+4Obv22zCCFMYnJx88knn7B06VL69et3aV9ERATBwcGMGjVKihshbkKKovDBgQ+I+TsGgFERoxgZMdIqhY1xRuJzQDXqSHz+KJxchyyQKcTNyeTiJisri8aNG1+xv3HjxmRlZZkllBDCehRF4e2/3uazY58BMKH1BIY0G2K15++Jy+J0eiEuDhoebBlktede1/YFxj+b9oNa9W2bRQhhMpP73ERERLBw4cIr9i9cuJCIiAizhBJCWIfeoGfGzhmXCpup7aZatbABLg3/7hcRhLtTNehInJMA/3xr3JalFoS4KZnccvP222/Tp08fNm7cSIcOHVCpVOzYsYOEhATWrl1riYxCCAvQGXRM2z6NX878glqlZkbHGTzY4EGrZsgq1PLr36kADGgXbtVnX9OuaDDooE4XCG5t6zRCiEowueWmW7duxMbG8tBDD5GTk0NWVhYPP/wwJ06coEuXLpbIKIQwM61ey8Q/JvLLmV+wU9nxVpe3rF7YAHy3LxGt3kDzYE+ah3ha/flXKMqCfZ8YtzuPs20WIUSlmdxyAxAUFCQdh4W4SZXoShi3ZRzbk7Zjr7ZnXvd5dA/tbvUciqLwxb9mJK4W/loGZYUQ0Bzq323rNEKISqpQcXP48GGaNWuGWq3m8OHD1z23RYsWZgkmhDC/wrJCnv/9ef5K/QtnO2cW9FhAh6AONsmy80wmZzIKcXO0o19ENehIrC2C3YuM253GQnUYtSWEqJQKFTctW7YkNTUVf39/WrZsiUqlQlGUK85TqVTo9XqzhxRCVF2eNo9nNz7L4fTDuNq7En13NK0CWtksz6oLMxL/r2UQro6VakQ2r4OroCgDvMLg9odsnUYIUQUV+okSFxeHn5/fpW0hxM0lqySLERtGcDzrOB4OHizuuZhmvs1slic9v5T1R6pRR2K9DnZcWCCz4xjQVINiSwhRaRX6FxwefvmHz7lz5+jYsSN2duUv1el07Nixo9y5QgjbSy9KJ2p9FKdzT+Pj5MOSnkto5NPIppm+2ZdAmV6hZagXTYM8bJoFgCPfQ048uPhCywG2TiOEqCKTR0v16NHjqpP15ebm0qNHD7OEEkKYR3JBMoN+G8Tp3NP4u/jz8X0f27ywMRgudyQeUB06EisK/Pmecbv9SHBwsW0eIUSVmdz2qijKVadHz8zMxNXV1SyhhBBVdy7vHJHrI0ktTCXYLZilvZYS4h5i61hsO5VBQlYx7k52PNCiGnQkPrkB0o6AgxvcGWnrNEIIM6hwcfPwww8Dxk7DgwcPxtHR8dIxvV7P4cOH6dixo/kTCiFMdir7FFEbosgozqCORx1iesVQ27W2rWMBXFpH6pFWITg7WHa18QrZfmGBzNaDwdnbplGEEOZR4eLG09M4wZaiKLi7u+Ps7HzpmIODA+3btycqKsr8CYUQJjmaeZQRG0aQU5pDQ++GLO65GF9nX1vHAuB8Xgkbj6UB1eSVVPxuOLcd1PbQYbSt0wghzKTCxc2KFSsAqFOnDi+++CIuLvJeWojq5mDaQUZtHEV+WT7NajVjUc9FeDpWg5l/L/jqrwT0BoU763hzW4C7reNcbrWJeBI8qsErMiGEWZjcoXjgwIEkJSVdsf/kyZOcPXvWHJmEEJWwJ2UPwzcMJ78sn1b+rYjpFfN/9u47PIpq/+P4e7OppEMgCSGURHrvNfSqIsJVUCnKlSYoTUW4iBQVFJCiUgMCNsACV/RHCyUQCN2EIqETQgkEAullN7vz+2Ml3kgxG3Z3Ur6v58nD7uzsnE+GwH5z5sw5haqwMRgV1uUOJC4Ed1UmnIGzmwGNLJApRDFjdnHz2muvmZfQJQAAIABJREFUERkZ+cD2Q4cO8dprr1kikxDCTBHXIhi5cySZOZm09G/Jks5LcHN0UztWHuFnE7iRnIV3KQe61ykE43/u99rUfBZ8qqqbRQhhUWYXN1FRUbRu3fqB7S1atCA6OtoioYQQ+bfjyg5G7x5NtiGb9hXa80WnLyjlUPguG9+fkfiFxhVwdlB5IPG9K3DiB9PjNuPVzSKEsDizixuNRkNqauoD25OTk2XpBSFs7NeLv/LOnnfIMebQvXJ35nWYh5PW6Z/faGPX7mWw+6xpIPHLzQrBQOLIL0AxQFAHCFBvCQohhHWYXdyEhIQwa9asPIWMwWBg1qxZtGnTxqLhhBCP9uO5H5m8bzIGxUCv4F58EvIJDnYOasd6qLWH41AUaP1UGYLKqny5LC0Bor4xPQ6RXhshiiOzJ/GbPXs2bdu2pXr16oSEhAAQERFBSkoKu3btsnhAIcSDvjn9DbOPzAbgpeovMan5JOw0Zv+uYhO6HCPrj1wFYEBhGEh8cDHkZEGFplA5RO00QggrMPt/w1q1anHixAn69u1LQkICqampDBo0iDNnzlCnjnoL8QlRUiw/sTy3sBlcZzD/af6fQlvYAGw/fZM7aTrKuTvRuZavumEyk+DwCtPjNuPhIbOtCyGKvgItfVu+fHlmzpxp6SxCiMdQFIXPoz5nxUnTh/PIBiMZUW/EQ5dDKUy+PWiakfilpoE4aFUuwo6sAF0qlKsF1bqrm0UIYTUFKm4AMjIyiIuLQ6fT5dler169Jw4lhMjLqBiZfWQ238V8B8A7Td7h1dqvqpzqn11ISOXgpbvYaeAltQcS6zLg4BLT4zbjwK7w9nYJIZ6M2cXN7du3GTx4MFu2bHno63LHlBCWZTAa+PDgh/x8/mcA3m/+Pv1q9FM5Vf7cv/27Yw1fynu5/MPeVhb1DWTcAa9KULuPulmEEFZl9q8uY8eO5d69exw8eBAXFxe2bt3KmjVrqFq1Kps2bbJGRiFKLL1Rz3/2/Yefz/+MncaOj1p/VGQKm0ydgZ+PXQNgQAuVe21ydKbbv8E0G7G2wJ3WQogiwOx/4bt27eKXX36hadOm2NnZUalSJbp06YKHhwezZs3imWeesUZOIUocnUHHu3veZdfVXdhr7Pmk7Sd0q9xN7Vj59uvxG6Rk5RBY2oW2VcuqG+bEeki+Cm6+0KC/ulmEEFZnds9Neno65cqVA6B06dLcvn0bgLp16/L7779bNp0QJVRmTiajd49m19VdONo5sqDDgiJV2AB8d8g0kPiVZpWws1Nx0LMhB/bNMz1uNRocnNXLIoSwCbOLm+rVq3P27FkAGjRowLJly7h+/TpLly7F39/f4gGFKGnS9emM3DGS/df342LvwpedvqRdYDu1Y5nl5LVkjl9LxlFrR98mFdQN88dGuHsJXEpDk8HqZhFC2ITZl6XGjh1LfHw8AFOnTqVbt2589913ODo6snr1akvnE6JESc5OZuSOkZy4cwI3BzcWdVpEI9+itzzANwdjAehR148ybiouB2E0QsRc0+OWI8HRVb0sQgibMbu46d//r+vVDRs2JDY2ljNnzlCxYkV8fHwsGk6IkuRu1l2Ghw3nzN0zeDp5sqzzMmr71FY7ltmSMnT8En0DgIEtVJ6R+Oz/we0z4OQJzYapm0UIYTNmXZbS6/UEBQVx+vTp3G2lSpWiUaNGUtgI8QQSMhIYvHUwZ+6eoYxzGb7q9lWRLGwAfjp2jewcIzX9PWhcyVu9IIoCe+eYHjcfBs6e6mURQtiUWcWNg4MD2dnZFp8RdfHixVSpUgVnZ2caN25MREREvt63bt06NBoNzz//vEXzCGFL19Ou8+qWV7mUfAnfUr6s7r6aat7V1I5VIEajwjd/zkg8qGUldWdPvrAD4o+DQylo/oZ6OYQQNmf2gOK33nqLTz/9lJycHIsEWL9+PWPHjmXy5MlERUUREhJCjx49iIuLe+z7rly5wjvvvJO7eKcQRdGVlCu8tvU1rqVdo4JbBdb0WENlz8pqxyqwvedvcyUxA3dne3o1KK9ekP/ttWnyb3Ato14WIYTNmT3m5tChQ+zcuZPt27dTt25dXF3zDtDbsGGDWcebN28er7/+OkOGDAFgwYIFbNu2jSVLljBr1qyHvsdgMNC/f3+mT59OREQESUlJ5n4bQqju/L3zDN0+lMSsRKp4ViG0Syi+riovLPmE7q8j9ULjCpRyVHGivNh9cPUQaJ2g1Vvq5RBCqMLs/328vLz417/+ZZHGdTodx44dY+LEiXm2d+3alcjIyEe+b8aMGZQtW5bXX3/9Hy9hZWdnk52dnfs8JSXlyUILYQF/JP7BiLARJGUnUc27Gsu7LKeMS9HuXbh6N4OdZxIAGKD2QOI9n5r+bDQQ3P3UzSKEsLl8FTebNm2iR48eODg4sGrVKos1fufOHQwGA76+eX9b9fX15ebNmw99z/79+1m5ciXR0dH5amPWrFlMnz79ibMKYSnRCdG8seMN0vRp1PWpy5LOS/B0KvqDXb8/HIeiQJunfAgu66ZekCuREBsBdg6mBTKFECVOvsbc9O7dO/fSj1arJSEhwaIh/j7oUFGUhw5ETE1NZcCAAYSGhub77qxJkyaRnJyc+3X16lWLZBaiIA7FH2JY2DDS9Gk09m3M8i7Li0Vhk6U3sP6I6d/WwJYq99qEf2L6s+EA8FR5AkEhhCry1XNTtmxZDh48SM+ePR9ZeBSEj48PWq32gV6ahISEB3pzAC5evEhsbCw9e/bM3WY0GgGwt7fn7NmzBAcH53mPk5MTTk4qTiImxJ/2XtvLuN3j0Bl1tCrfigUdFuBir/JK2Ray+WQ8d9N1lPd0plONcuoFiTsIl/eYem1CxquXQwihqnz13IwYMYJevXqh1WrRaDT4+fmh1Wof+mUOR0dHGjduTFhYWJ7tYWFhtGrV6oH9a9SowcmTJ4mOjs79eu655+jQoQPR0dEEBgaa1b4QthJ2JYwxu8egM+roENiBLzp+UWwKGyD39u9XmlfEXmv2TZiWc3+sTYNXwEvllciFEKrJV8/NtGnTeOmll7hw4QLPPfccq1atwsvLyyIBxo8fz8CBA2nSpAktW7Zk+fLlxMXFMWLECAAGDRpEQEAAs2bNwtnZmTp16uR5//0cf98uRGHx68VfeX//+xgVIz0q9+DjkI9xsHNQO5bFnLiWRFRcEg5aDf2aqlhQXD0CF3eBnT2EvK1eDiGE6vJ9t1SNGjWoUaMGU6dO5cUXX6RUqVIWCdCvXz8SExOZMWMG8fHx1KlTh82bN1Opkum6fVxcHHZ2Kv4mKMQT+OHsD3x08CMUFHo/1ZupLaeitTOvh7OwWx0ZC8Cz9cpT1l3FS8B7/hxrU/9l8FZ53I8QQlUaRVEUtUPYUkpKCp6eniQnJ+Ph4aF2HFGMff3H18w5appI7uUaLzOx2UTsNMWrUL+Tlk2rWbvQGYz8Mqo19QMt06NrtmvHYEVH0GjhrWNQuoo6OYQQVmPO57eKs2wJUTwpisLyE8v5MvpLAP5d59+MbTRW3aUIrGTtoTh0BiMNAr3UK2zgr7E29V+SwkYIIcWNEJakKAoLf1/IylMrAXizwZsMqzesWBY2eoORbw+ZBhK/1qqyekGuHYPz20BjJ2NthBCAFDdCWIxRMfLp4U/5/sz3ALzb5F0G1R6kcirr2XrqJrdSsinr7sTTdf3VCxI+0/Rn/ZehTPDj9xVClAhmDQDQ6/V06NCBc+fOWSuPEEWSwWhgWuQ0vj/zPRo0TGkxpVgXNgBr/hxI/EqzijjaqzSWKO6QafVvO3to+646GYQQhY5ZPTcODg6cOnWqWHaxC1FQeqOeyfsms+XyFuw0dnzU+iN6Bvf85zcWYaeuJ3P0yj3s7TT0b67i7d+7Pzb92aC/jLURQuQy+9etQYMGsXLlSmtkEaLI0Rl0vB3+Nlsub8FeY8+ctnOKfWEDf93+/Uw9f8p5OKsTInbfX7MRt31HnQxCiELJ7DE3Op2OFStWEBYWRpMmTXB1dc3z+rx58ywWTojCLDMnk7G7xxJ5IxJHO0fmd5hP2wpt1Y5ldYlp2Ww6fgOAV9UaSKwosPvPsTaNBslsxEKIPMwubk6dOkWjRo0AHhh7I5erREmRrk9n1M5RHLt1DBd7F77o+AXN/ZurHcsm1h6OQ5djpH4FTxqqdfv35T1wZT9oneQOKSHEA8wubnbv3m2NHEIUGcnZybyx4w1O3jmJm4MbSzovoUG5BmrHsgldjpGvD/x5+3fryur8QqMosOvPsTZNBoNngO0zCCEKtQLf4nDhwgW2bdtGZmYmYJrfQ4jiLjEzkde3vc7JOyfxdPJkRbcVJaawAfi/kzdISM2mnLsTz9Qtr06ICzvh2mGwd4Y249TJIIQo1MwubhITE+nUqRPVqlXj6aefJj4+HoAhQ4bw9tvSPSyKr1vptxi8bTBn752ljHMZVnVbRe0ytdWOZTOKorBy32XANNZGldu/FQV2zTA9bjoE3P1sn0EIUeiZ/b/TuHHjcHBwIC4uLs/imf369WPr1q0WDSdEYXE97TqvbX2Ny8mX8XP1Y02PNVT1rqp2LJs6fPkup66n4OxgxyvNVBrAe/oXiD8Ojm7SayOEeCSzx9xs376dbdu2UaFChTzbq1atypUrVywWTIjCIjY5liHbh3Ar4xYV3CqwsttKyrupdElGRfd7bfo0qoC3q6PtAxhyYNdHpsctR4Grj+0zCCGKBLOLm/T09Dw9NvfduXMHJycni4QSorA4f+88Q7cPJTErkSDPIEK7hlKuVDm1Y9nclcR0wmJuAfDv1pXVCXF8LSSeB5fS0PJNdTIIIYoEsy9LtW3blq+//jr3uUajwWg0MmfOHDp06GDRcEKo6Y/EPxi8bTCJWYnUKF2DVd1XlcjCBmDV/lgUBdpVK8tT5dxtHyAnG8I/MT0OGQ/OHrbPIIQoMszuuZkzZw7t27fn6NGj6HQ6JkyYwB9//MHdu3fZv3+/NTIKYXNRCVGM3DGSNH0a9XzqsbjzYjydPNWOpYqULD0/Hr0KwOttVFri4OhXkHIN3MubBhILIcRjmN1zU6tWLU6cOEGzZs3o0qUL6enp9OnTh6ioKIKDZUVeUfQdjD/I8LDhpOnTaOzbmOVdl5fYwgZg/eGrpOsMVPN1I6SqCuNcslNh71zT43YTwMHF9hmEEEWK2T03cXFxBAYGMn369Ie+VrGiTIMuiq691/Yybvc4dEYdrcu3Zn6H+bjYl9wP0xyDMXcdqX+3rqLOpH0Hl0LGHSgdBA0H2L59IUSRY3bPTZUqVbh9+/YD2xMTE6lSRVblFUXXtthtjNk1Bp1RR8fAjnze8fMSXdgAbD51k+tJmZR2deT5hirMBJxxFyI/Nz3uMBm0DrbPIIQocswubhRFeehvb2lpaTg7q7Q6sBBPaNPFTUzYO4EcJYceVXowt/1cHLUq3O5ciCiKwvK9FwF4tWVlnB20tg+xdw5kp4BvXajdx/btCyGKpHxflho/fjxgujtqypQpeW4HNxgMHDp0iAYNSs409KL4+OHsD3x48EMA+lTtwwctPkBrp8IHeSFz4GJi7qR9A1tWsn2Ae7FwONT0uOsMsFNhRmQhRJGU7+ImKioKMP02d/LkSRwd//qt1tHRkfr16/POO+9YPqEQVrTmjzXMPWoarNq/Zn8mNJ2AnUY+RAGW7b0EQN8mgZRWY9K+nR+CUQ9BHSC4o+3bF0IUWfkubu6vBj548GAWLlyIh4fMMyGKLkVRWHpiKYujFwMwpO4QRjccrc6A2UIoJj6FPeduY6eBIW2CbB/g+u9w6idAA10evHlBCCEex+y7pVatWmWNHELYjKIozP99PqtOmX6W32r4FsPqDVM5VeES+mevTY86/lQs8+CM5FalKBD2gelxvX7gX9+27QshijyzixuAI0eO8OOPPxIXF4dOp8vz2oYNGywSTAhrMCpGPjn8CWvPrAVgQtMJDKw1UOVUhcuNpEw2Hb8BwLC2KvTanA+D2AjQOkHHybZvXwhR5Jk9uGDdunW0bt2a06dPs3HjRvR6PadPn2bXrl14epbcic5E4WcwGpgaOZW1Z9aiQcMHLT+QwuYhVu2/TI5RoUVQaeoHetm2caPhr16b5sPBS+bNEkKYz+ziZubMmcyfP5/ffvsNR0dHFi5cSExMDH379pUJ/EShpTfqmRgxkf9e+C9ajZaP23zMi9VeVDtWoZOSpWftYdNSC8PbqjDjePT3cDsGnL1Ma0gJIUQBmF3cXLx4kWeeeQYAJycn0tPT0Wg0jBs3juXLl1s8oBBPKtuQzfjw8WyN3Yq9nT1z2s2hZ3BPtWMVSt8djCMtO4dqvm60r17Wto1np8Eu0y35tH0HXLxt274Qotgwu7gpXbo0qampAAQEBHDq1CkAkpKSyMjIsGw6IZ5QZk4mb+18i/Cr4ThpnVjYYSFdKnVRO1ahlKU3sHLfZQCGtQ22/Z1j+xdA2i3wrgzNZIC3EKLgzB5QHBISQlhYGHXr1qVv376MGTOGXbt2ERYWRqdOnayRUYgCSdOlMWrnKH5P+B0Xexe+7PglzfybqR2r0Prh6FXupGUT4OVCrwblbdt4UhxEfmF63PUjsHeybftCiGLF7OLmyy+/JCsrC4BJkybh4ODAvn376NOnD1OmTLF4QCEKIjk7mRFhIziVeAp3B3cWd15Mg3Iyg/aj6A1Glu0x3f49vF0QDlobT2S4YxrkZEGlNlDjWdu2LYQodjSKoihqh7CllJQUPD09SU5OlokIi6nEzESGhQ3j3L1zeDl5sazLMmqVqaV2rELtx6NXefenE/i4ObHvvQ62XUcq7hB81RXQwPA9Mq+NEOKhzPn8NvvXs/79+xMaGsq5c+cKHFAIa7mVfovXtr7GuXvn8HHxYVW3VVLY/AODUWHJHtMCmUNCqti2sDEaYdsk0+OGA6SwEUJYhNnFjZubG5999hk1atSgfPnyvPzyyyxdupQzZ85YI58Q+XYt9Rqvbn2V2JRY/Fz9WN19NU95P6V2rEJv66mbXLqdjoezPQNa2HiBzJM/wvVj4OgGHeWythDCMswubpYtW8aZM2e4ceMG8+bNw9PTk4ULF1K7dm38/f2tkVGIf3Q5+TKvbX2N62nXCXQPZE33NVTyUGEl6yJGURQW7b4AwGutq+DmVKBJywtGl24aawOmOW3cfW3XthCiWCvw/2Tu7u54e3vj7e2Nl5cX9vb2+Pn5WTKbEPly9u5ZhoUN427WXYI9gwntGkrZUjaeo6WICj97m9PxKZRy1DK4VWXbNh4xD1JvgGdFaDHKtm0LIYo1s3tu3nvvPVq0aIGPjw/vv/8+Op2OSZMmcevWLaKioqyRUYhHOnXnFP/e9m/uZt2lRukafNX9Kyls8klRFL78s9emf/OKeLs62q7xxIsQ+bnpcfeZ4OBsu7aFEMWe2T03c+bMoWzZskydOpVevXpRs2ZNa+QS4h/9fut3Ru4cSbo+nXpl67Gk8xI8HOUOuPw6cDGRY1fu4ai1Y2iIDRfIVBTY8h4YdBDcUW79FkJYnNnFTVRUFHv27CE8PJzPPvsMrVZLu3btaN++Pe3bt5diR9jEgRsHGLN7DJk5mTT1a8oXHb/A1cFV7VhFhqIozN9huuPx5WaBlPOwYc/J2S1wIQzsHKDHHLD1TMhCiGLP7OKmfv361K9fn9GjRwNw/PhxFixYwOjRozEajRgMBouHFOJ/hV8N5+3wt9EZdbQOaM2C9gtwtpfLGubYfyGRI7H3cLS34432NryjTJ8JW98zPW71JvjI3WxCCMsr0IDiqKgowsPDCQ8PJyIigpSUFBo0aECHDh0snU+IPLbGbmXS3knkKDl0qtiJ2W1n46i14ViRYuB/e21eaVYRP08bFob7F5qWWvAIgLbv2q5dIUSJYnZx4+3tTVpaGvXr16d9+/YMHTqUtm3bymy/wup+ufALH0R+gFEx8kzQM3zU+iPs7Wx463IxEXH+Dseu3MPJ3o432gfbruF7sbBvvulx14/AUS4jCiGsw+xPhm+++UaKGWFz686s4+NDHwPwr6r/YkqLKWjtbDiTbjGRp9emeUV8bTXWRlFgy0TT+lFV2kLt3rZpVwhRIpld3Dz7rNzZIGxr9anVfHbsMwAG1BzAhKYT0Mgg1ALZc+42UXFJpl6bdjbstTnzG5zbIoOIhRA2IX36otBSFIWlx5ey+PhiAIbWHcpbDd+SwqaAFEVhwY7zAAxoUcl2d0hlpcDmCabHrcdAuRq2aVcIUWJJcSMKJUVRmH9sPqv+WAXA6IajGVpvqMqpirbwc7eJvpqEs4MdI2zZa7PrI9NMxKWDoO07tmtXCFFiSXEjCh2jYmTmoZmsP7segPeavseAWgNUTlW0GY0K87abxtoMbFGJsu5Otmn4+jE4vNz0+Jl54OBim3aFECWaFDeiUDEYDUyNnMovF39Bg4YPWn7AC9VeUDtWkbfl1E1OXk/G1VFru14bQw78OgZQoF4/CJapIoQQtiHFjSg09EY9kyImsS12G1qNlo/afMSzQTKA/UnpDUbmbj8LwNC2QZRxs1GvzaElcPMkuHhDt5m2aVMIIZDiRhQS2YZs3gl/h/Br4djb2TO37Vw6Veqkdqxi4cej17h8J50yro4MsdUaUveuwO4/C5ouH4Krj23aFUIIpLgRhUCGPoMxu8dwMP4gTlonFnRYQJuANmrHKhYydQYW7jSNtXmz41O4Odngn7yimC5H6TOgUhtoKOOlhBC2JcWNUFWaLo1RO0fxe8LvuNi7sKjTIpr6NVU7VrGxOjKWWynZVPB24ZXmFW3T6O9fw6XdYO8Mz30uc9oIIWxOihuhmuTsZIaHDeePxD9wd3BnSZcl1C9bX+1YxUZyhp4l4RcAGN+lGk72NpjROfkabJtsetxxCpSx4S3nQgjxJyluhCruZN5hWNgwzt87j7eTN8u6LKNmmZpqxypWlu69SEpWDtV93enVIMD6Dd6/HKVLhQrNoMUb1m9TCCEeQoobYXM3028ydPtQYlNiKetSltCuoQR7yW/4lnQzOYtV+y8D8G636mjtbHBpKPp7uLADtE7QaxHI2l9CCJVIcSNs6mrqVYZuH8r1tOv4u/qzousKKnrYaCxICTJn21my9EaaVPKmU81y1m8w5QZsnWR63OE/ULaa9dsUQohHsFM7AMDixYupUqUKzs7ONG7cmIiIiEfuGxoaSkhICN7e3nh7e9O5c2cOHz5sw7SioC4lX+K1ra9xPe06Fd0rsqb7GilsrODktWR+/v0aAFOerWX9tbgUBX4bB9nJUL4RtHzTuu0JIcQ/UL24Wb9+PWPHjmXy5MlERUUREhJCjx49iIuLe+j+4eHhvPzyy+zevZsDBw5QsWJFunbtyvXr122cXJjj7N2zDN46mISMBII9g1ndfTX+bv5qxyp2FEVhxm9/ANC7YQD1A72s3+ix1XBuK2gd4fnFoJUOYSGEujSKoihqBmjevDmNGjViyZIludtq1qzJ888/z6xZs/7x/QaDAW9vb7788ksGDRr0j/unpKTg6elJcnIyHh4eT5Rd5M+pO6cYHjacFF0KNUvXZFmXZXg7e6sdq1jafDKekd/9jrODHbvfaY+/p5XXckq8CEvbmOa06foRtHrLuu0JIUoscz6/Ve250el0HDt2jK5du+bZ3rVrVyIjI/N1jIyMDPR6PaVLl37o69nZ2aSkpOT5ErZz7NYxhmwfQoouhfpl67Oi2wopbKwkS29g1pYYAIa3DbZ+YWPQw4ahpsKmcgi0GGXd9oQQIp9ULW7u3LmDwWDA19c3z3ZfX19u3ryZr2NMnDiRgIAAOnfu/NDXZ82ahaenZ+5XYGDgE+cW+RN5I5IRYSNI16fTzK8Zy7ssx8NResusZdX+WK7ezcTXw4nh7WywzMLeuaZVv509ofdSsFP9KrcQQgCFYMwN8MCAR0VR8jUIcvbs2axdu5YNGzbg7Oz80H0mTZpEcnJy7tfVq1ctklk8XvjVcN7c+SZZhixCAkJY1GkRpRxKqR2r2Lqdms2i3aYJ+yZ0q0EpRyuPe7l6BPbOMT1+Zh54VrBue0IIYQZVR/75+Pig1Wof6KVJSEh4oDfn7+bOncvMmTPZsWMH9erVe+R+Tk5OODnZaBVkAcDWy1uZFDGJHCWHLpW68GnIpzhoHdSOVazNCztLWnYO9Sp40ruhlSfsy04zXY5SDFD3Raj7gnXbE0IIM6nac+Po6Ejjxo0JCwvLsz0sLIxWrVo98n1z5szhww8/ZOvWrTRp0sTaMYUZNp7fyHsR75Gj5PBs0LPMbjtbChsri76axLojph7JKc/Wws7aE/ZtmQD3LoNHBXh6rnXbEkKIAlD9ns3x48czcOBAmjRpQsuWLVm+fDlxcXGMGDECgEGDBhEQEJB759Ts2bOZMmUK33//PZUrV87t9XFzc8PNzU2170PA2jNrmXloJgAvVHuBKS2mYKcpFFc+iy2DUeH9/55EUaBPowCaVn74wHqLiV4L0d+Bxg76LAMXG9xqLoQQZlK9uOnXrx+JiYnMmDGD+Ph46tSpw+bNm6lUqRIAcXFx2P3PQMXFixej0+l44YW8XeFTp05l2rRptowu/seqU6uYd2weAANqDmBC0wnWnzxO8N2hK5y6noK7sz2Telh5ba7b5+D/xpset58EldtYtz0hhCgg1ee5sTWZ58ayFEVh8fHFLD2+FIBh9YbxZoM3pbCxgdup2XT8LJzUrBw+7FWbgS0rW68xfSaEdoKEP6BKWxj4X1k7SghhU+Z8fqvecyOKLkVR+OzoZ6w5vQaAMY3GMKTuEJVTlRyzNseQmpVD3QBPXmleybqNbXnPVNi4loM+K6SwEUIUalLciAIxKkZmHprJ+rPrAZjYbCL9a/ZXOVXJcfBSIhuirqPRwIfP17Huqt8nf4Lf1wAa6LMc3B9/J6MQQqhNihththxjDlMjp7Lp4iY0aJgyM67uAAAgAElEQVTWahp9qvZRO1aJoTcYmfLfUwC80qwiDay5ftTts/DrGNPjtu9AcAfrtSWEEBYixY0wi96gZ2LERLZf2Y5Wo2Vmm5k8HfS02rFKlOV7L3E+IY3Sro6826269RrKSoZ1r4AuzbS8QruJ1mtLCCEsSIobkW/ZhmzeDn+bPdf24GDnwJx2c+hUsZPasUqUCwmpLNxxHoD3n6mJVylH6zRkNMKG4ZB4wTSfzQurZLVvIUSRIf9biXzJ0GcwevdoDsUfwknrxMIOC2kd0FrtWCWKwajw7k8n0BmMdKhe1rozEe+dA+e2gNYJ+n0DbmWt15YQQliYFDfiH6XqUhm1cxRRCVGUsi/Fl52+pKlfU7VjlTir9l8mKi4Jdyd7Zvapa73b7c9uhXDTZIw8Ox8CGlmnHSGEsBIpbsRjJWUlMXzHcE4nnsbd0Z2lnZdSr+yj1/IS1hF7J525288C8J9nauLv6WKdhu5cMK0bBdB0KDSUO+CEEEWPFDfike5k3mHo9qFcSLqAt5M3y7sup0bpGmrHKnGMRoWJG06QpTfS+qkyvNQ00DoNZdyFtf0gOwUCW0C3mdZpRwghrEyKG/FQN9NvMnT7UGJTYinrUpYVXVcQ5BWkdqwS6fvDcRy8dBcXBy2f9KlnnctROTpYP9A0gNgzEPp+DfZWGqwshBBWJsWNeMDV1KsM2TaEG+k3KO9anhVdVxDoYaXeAvFYsXfSmbk5BoAJ3asTWLqU5RtRFNNcNlf2gaM7vLJeJuoTQhRpUtyIPC4lX2LotqEkZCZQyaMSoV1C8XfzVztWiaQ3GBmzPpoMnYHmVUozyFprR+2bB8e/N630/eJq8K1tnXaEEMJGpLgRuc7ePcuwsGHczbrLU15PEdo1FB8XH7VjlVif7zzP8atJeDjbM79fA+sssfDHRtg5w/S4x2yo2tnybQghhI1JcSMAOHn7JMN3DCdVl0qtMrVY1nkZXs5WnNZfPNbhy3dZtPsCADP71KW8lxXujroSCRtHmB63GAnNhlq+DSGEUIGd2gGE+o7ePMrQsKGk6lJpULYBK7qukMJGRcmZesatj8aowL8aVeDZeuUt38jNk/D9S5CTBdWfhq4fWb4NIYRQiRQ3JVzk9Uje2PEG6fp0mvs1Z1mXZbg7uqsdq0T74JdTXE/KpGLpUkx7rpblG7h7Gb79F2QnQ8WW8MJXYKe1fDtCCKESKW5KsF1xu3hz15tkGbJoW6EtX3b6klIOVrgbR+TbT8eu8Uv0DbR2Gub3a4C7s4NlG0hLgG96Q9ot8K0DL68DBytNCCiEECqR4qaE2nJ5C+PDx6M36ulSqQsL2i/A2d5Z7Vgl2ukbKUzeeBKAMZ2q0riSt2UbyEqGb/vAvcvgVQkG/AwucvlRCFH8SHFTAm08v5H39r6HQTHQM6gns9vOxkFr4R4CYZbkTD1vfHeM7Bwj7aqV5c0OT1m2gew0+L6faayNazkYuBHc/SzbhhBCFBJyt1QJ833M98w6PAuAvtX6MrnFZOw0UuOqyWhUePuH41xJzCDAy4UF/RpgZ8nbvnXp8H1fiDsAzp4w4CcoE2y54wshRCEjxU0JsvLkShb8vgCAQbUG8U6Td6y3srTIt6V7L7Ij5haOWjuWDGiEt6sFlz3QZZh6bK7sBydPU4+Nf33LHV8IIQohKW5KAEVRWBS9iGUnlgEwov4IRtYfKYVNIbD/wh3mbjOt9j29V23qVbDgGBhdhmkhzNgIcPKAgRsgoLHlji+EEIWUFDfFnKIozD06l69Pfw3A2EZjeb3u6yqnEgBX72bw1toojAq80LiCZVf71mXAupfh8l5wdDMNHq7QxHLHF0KIQkyKm2LMqBj5+ODH/HDuBwAmNZvEKzVfUTmVANMA4sGrj3A3XUedAA8+er6O5XrSMpNg7UumMTYOrqbCJrCZZY4thBBFgBQ3xVSOMYcP9n/Ar5d+RYOG6a2m07tqb7VjCUwLYr75/e9cSEjDz8OZFYOa4uxgoUn00m7Dt71Nd0U5eUL/H6Fic8scWwghiggpboohvUHPexHvEXYlDK1Gy6yQWfSo0kPtWALTZcKpm/4g4vwdSjlqWfFqE/w8LTS/UNJV+OZ5SLwArmVNg4f96lrm2EIIUYRIcVPMZOVkMT58PBHXI3Cwc2Buu7l0rNhR7VjiTyv3Xeb7Q3FoNPD5Sw2pE+BpmQPfOQ9fPw8p18AzEAb9Ird7CyFKLCluipEMfQajd43m0M1DOGudWdhhIa0CWqkdS/xp66l4Pt4cA8D7z9Sicy1fyxz4SiSsewUy74FPNRj4X/AMsMyxhRCiCJLipphI1aUycsdIom9HU8q+FIs6LaKJn9wdU1hEnL/N6LXRKAoMaFGRf7eubJkDn/gBfhkFBp3pNu9XfgBXH8scWwghiigpboqBe1n3GB42nJi7Mbg7urOs8zLqlpWxFoXF0di7DPv6GDqDkR51/JjWs/aT3xmlKLBnNoTPND2v2RN6LwdHWfhUCCGkuCni7mTeYej2oVxIukBp59Is77Kc6qWrqx1L/OnU9WQGrz5Cpt5A22plWfBSA+y1T7jcRU42/DoGjq81PW81GjpPBztZRkMIIUCKmyLtZvpNhmwfwpWUK5RzKUdot1CCPIPUjiX+dCEhjVe/OkxqVg5NK3uzbEBjnOyf8Jbv5GvwwyC4fgw0WnhmLjT5t2UCCyFEMSHFTRF1NeUqQ7YP4Ub6DQLcAgjtGkqguwVnuBVP5NLtNAasOETin5P0rXytKS6OT1jYXN4LPw6GjDvg7AUvfAVPdbJMYCGEKEakuCmCLiZdZOj2odzOvE1lj8qEdg3Fz9VP7VjiT2dvptJ/xSHupGXzVDk31gxuhoezQ8EPqCgQ+QXsmAaKwTR3Tb9vwbuypSILIUSxIsVNEXPm7hmGbR/Gvex7POX1FKFdQ/FxkbtjCosT15IY9NVhkjL01PBz59shzSnj5lTwA2beg02jIWaT6Xn9l+GZeTJwWAghHkOKmyLkxO0TjNgxglRdKrXK1GJZ52V4OVtwFWnxRI7E3mXwqiOkZedQP9CLNYOb4lXKseAHjN0PG4aZJuazs4fun0DTISCruQshxGNJcVNEHLl5hDd3vklGTgYNyzVkUadFuDu6qx1L/GnvudsM/+YYmXoDzaqU5qvXmuLmVMB/XgY97PkUIj4DxQilg+BfK0zz2AghhPhHUtwUAfuv72fM7jFkG7Jp4d+ChR0WUspBLksUFt8fimPKL6cwGBXaVivLsgGNCz54OPEibBwO146YnjcYAD0+BSc3ywUWQohiToqbQm5n3E7e3fMueqOedhXa8Vn7z3DSPsEYDmExBqPCJ1tiCI24DEDvhgF88q+6Bbvd25ADBxfB7pmQk2Va0bvnfKjzLwunFkKI4k+Km0Js86XN/GfffzAoBrpW6sonIZ/goH2Cu26ExWTochizLpqw07cAGN+lGm91fKpgMw/f+sO0hMKNKNPzoPbw3BfgVdFieYUQoiSR4qaQ2nB+A9Mip6Gg8Fzwc0xvNR17O/nrKgyu3s1gxLfH+ONGCo72dsx9sT7P1S9v/oH0mRAxD/bNB6Pe1FvT7WNoOEAGDQshxBOQT8tC6LuY7/jk8CcA9Kvej/80/w92GplavzDY9sdN3v3xOClZOZRxdWT5oCY0ruRt3kEUBWJ+hW2TITnOtK3Gs/D0XPDwt3xoIYQoYaS4KWRWnFzBwt8XAvBqrVd5u8nbT77Ionhiuhwjn249w8p9pvE1DSt68eUrjQjwcjHvQAlnYOt7cCnc9Nyjgqm3plYv6a0RQggLkeKmkFAUhS+iviD0ZCgAb9R/gzfqvyGFTSFw9W4Gb62NIvpqEgBDQ6owoXsNHMxZADP1FuydA8dWgTEHtE7QejS0GQeOrlZKLoQQJZMUN4WAoijMPjKbb2O+BWB84/EMrjNY5VTCaFT4/nAcszbHkK4z4OFsz2d9G9Cllm/+D5KZBJGfw8EloM8wbav+NHSbCaWrWCe4EEKUcFLcqMyoGPnw4If8dO4nACY3n8xLNV5SOZWIS8zgvZ9PcOBSIgBNKnkzv18DAkvnc36h7FQ4stI0WDjL1ONDQGPoNBWC2lkptRBCCJDiRlU5xhym7J/Cb5d+w05jx/RW03n+qefVjlWiGYwKXx+IZfbWs2TqDbg4aJnQvTqDWlZGa5ePS4QZd+HQUji07K+ixqc6dPoAajwj42qEEMIGpLhRid6g572I9wi7Eoa9xp5ZIbPoXqW72rFKtMiLd5jx62nO3EwFoEVQaT79Vz0qlcnHmJikq6ZLT8dWgz7dtK3MUxDyNtTrB3YFnLFYCCGE2aS4UUFWThbjw8cTcT0CBzsH5rWfR/vA9mrHKrGuJKbz8f/FsP3PCfk8nO15t3sN+jeriN3jemsUBWIjTL00Zzeb1oEC8KsHIeOh5nNS1AghhAqkuLGxDH0Gb+16i8M3D+OsdWZhx4W0Kt9K7VglUkJKFsv2XuKbA1fQGYxo7TQMaF6RsZ2r4e36mNW8M+/ByZ/gyAq4feav7ZVDoPVYeKqTXH4SQggVSXFjQym6FEbuGMnx28dxdXBlUadFNPaVlZ5tLT45k2V7LrH2cBzZOabelrbVyjLlmZpU9X3ESuuGHLi4C45/D2c2gyHbtN3BFeq/BM2GQrmaNvoOhBBCPI4UNzZyL+sew8OGE3M3Bg9HD5Z1WUYdnzpqxypRLt5O46t9l/nx6DV0BlNR06iiF2M6V6NtVZ8H5xQyGuHaYTj9C5z6GdJu/fVaudrQaCA0eAWcPW34XQghhPgnUtzYwO2M2wwLG8aFpAuUdi7N8i7LqV66utqxSoQcg5EdMbf45uAV9l9IzN3evEppRneqSqvgMnmLGoMe4g5CzCY4vQnSbv71WqkyUPdFU0HjV08uPQkhRCElxY2VxafFM2T7EOJS4yhXqhyhXUMJ8gxSO1axdyEhlU3RN/jh6DVupmQBYKeBjjV8GRpSheZBZf7aOfk6XAiDCzvg0h7ITvnrNScPqN7DtDzCU13A/jFjcYQQQhQKUtxYUVxKHEO2DyE+PZ4AtwBWdF1BBfcKascqtuISM/j1xA1+PX4j93ZugDKujrzULJCXm1WkgncpSLkBJ36EK/tNX3fO5T1QqTJQ7c+CJqgd2DvZ+DsRQgjxJKS4sRSDASIiID4e/P25WLc8Q3eO4HbmbSp7VCa0ayh+rn5qpyxWsvQGDl++y95zt9lz7jbnE9JyX3PQamhbtSy963jRtXQCjrd2ws7f4fpRuBf7tyNpoEITU89M1c7g3xDsZBV2IYQoqgpFcbN48WLmzJlDfHw8tWvXZsGCBYSEhDxy/59//pkpU6Zw8eJFgoOD+fjjj+ndu7cNE//Nhg0wZgxcuwZATEVnhr8XxD1XO6p6V2V5l+X4uPiol6+YuJeuI/pqElFx94i6msThy3dz73bSYiDYLoGe/sl0KpNIdc01HO+ehf8799f8M/dp7ExjZiq1hsqtoWJLKFVahe9ICCGENahe3Kxfv56xY8eyePFiWrduzbJly+jRowenT5+mYsWKD+x/4MAB+vXrx4cffkjv3r3ZuHEjffv2Zd++fTRv3tz238CGDfDCC6YJ3YDjwS688XZlUkvZUedSBkvr9cFTChuzZOkNXLqdzoXbaVy4lcr5hDTOxSeRkXgdf00ifpq7VNMk0klzm+out6nqkEBp/S3slBxIxPT1v9z9oXwjCGho+rNCE7nDSQghijGNovz5qayS5s2b06hRI5YsWZK7rWbNmjz//PPMmjXrgf379etHSkoKW7Zsyd3WvXt3vL29Wbt27T+2l5KSgqenJ8nJyXh4eDxZeIMBKlfO7bE5UsOVN8dUJMNFS6Oz6Xy5II5SXmVJ2LcTtCVzplqjQSHHoEOvzyEnJ4ecHD2ZmelkpqeTlZlOdmY62ZlpZKUlkZORBFkp2OtT8dKkUYZUymiSKa1JxZtUtJp/+FG1d4Gy1aFcLdOcM+VqgW9t8PC3zTcrhBDCasz5/Fa150an03Hs2DEmTpyYZ3vXrl2JjIx86HsOHDjAuHHj8mzr1q0bCxYseOj+2dnZZGdn5z5PSUl56H4FEhGRW9hE1nZl9JhKZDva0eJUGgs/v0IpnQKZN/Gf0RQqq95JVnQ84lQpdvZo3MuDZwB4lAfPQCgTDKWDTF9ufjJWRgghhLrFzZ07dzAYDPj6+ubZ7uvry82bNx/6nps3b5q1/6xZs5g+fbplAv9dfHzuQ7+7elyzjLT8I425i6/ipP+rl0GXaodRcbBOhkJGQfPAc4PGDiNajNihaOzQaxzJsXPCqHXCqHUGBxdw9sChlBdOrl64enjj5OGDxrUsuPpAKR9wLWt6LsWLEEKIf1AouhP+PjOsoigPzhZbwP0nTZrE+PHjc5+npKQQGBj4BGn/h/9flzuC4nV8++El/O7qcDDk3c3xrV+hfXvLtCmEEEKIx1K1uPHx8UGr1T7Q65KQkPBA78x9fn5+Zu3v5OSEk5OV5ikJCYEKFeD6dVAUAm/r8r6u0Zhef8ydX0IIIYSwLFX7+B0dHWncuDFhYWF5toeFhdGq1cNXym7ZsuUD+2/fvv2R+1uVVgsLF5oe/73n6P7zBQtK7GBiIYQQQg2qD2AYP348K1as4KuvviImJoZx48YRFxfHiBEjABg0aBCTJk3K3X/MmDFs376dTz/9lDNnzvDpp5+yY8cOxo4dq8430KcP/PQTBATk3V6hgml7nz7q5BJCCCFKKNXH3PTr14/ExERmzJhBfHw8derUYfPmzVSqVAmAuLg47P5nEGmrVq1Yt24d77//PlOmTCE4OJj169erM8fNfX36QK9eeWYoJiREemyEEEIIFag+z42tWXSeGyGEEELYhDmf36pflhJCCCGEsCQpboQQQghRrEhxI4QQQohiRYobIYQQQhQrUtwIIYQQoliR4kYIIYQQxYoUN0IIIYQoVqS4EUIIIUSxIsWNEEIIIYoV1ZdfsLX7EzKnpKSonEQIIYQQ+XX/czs/CyuUuOImNTUVgMDAQJWTCCGEEMJcqampeHp6PnafEre2lNFo5MaNG7i7u6PRaCx67JSUFAIDA7l69aqsW2VFcp5tQ86zbch5th0517ZhrfOsKAqpqamUL18+z4LaD1Piem7s7OyoUKGCVdvw8PCQfzg2IOfZNuQ824acZ9uRc20b1jjP/9Rjc58MKBZCCCFEsSLFjRBCCCGKFe20adOmqR2iONFqtbRv3x57+xJ3xc+m5Dzbhpxn25DzbDtyrm1D7fNc4gYUCyGEEKJ4k8tSQgghhChWpLgRQgghRLEixY0QQgghihUpboQQQghRrEhxY6bFixdTpUoVnJ2dady4MREREY/d/+eff6ZWrVo4OTlRq1YtNm7caKOkRZs55zk0NJSQkBC8vb3x9vamc+fOHD582IZpiy5zf57vW7duHRqNhueff97KCYsHc89zUlISo0aNwt/fH2dnZ2rWrMnmzZttlLboMvc8L1iwgOrVq+Pi4kJgYCDjxo0jKyvLRmmLpr1799KzZ0/Kly+PRqPhv//97z++Z8+ePTRu3BhnZ2eCgoJYunSp9YMqIt/WrVunODg4KKGhocrp06eVMWPGKK6ursqVK1ceun9kZKSi1WqVmTNnKjExMcrMmTMVe3t75eDBgzZOXrSYe55feeUVZdGiRUpUVJQSExOjDB48WPH09FSuXbtm4+RFi7nn+b7Y2FglICBACQkJUXr16mWjtEWXuec5OztbadKkifL0008r+/btU2JjY5WIiAglOjraxsmLFnPP87fffqs4OTkp3333nXL58mVl27Ztir+/vzJ27FgbJy9aNm/erEyePFn5+eefFUDZuHHjY/e/dOmSUqpUKWXMmDHK6dOnldDQUMXBwUH56aefrJpTihszNGvWTBkxYkSebTVq1FAmTpz40P379u2rdO/ePc+2bt26KS+99JLVMhYH5p7nv8vJyVHc3d2VNWvWWCNesVGQ85yTk6O0bt1aWbFihfLqq69KcZMP5p7nJUuWKEFBQYpOp7NFvGLD3PM8atQopWPHjnm2jR8/XmnTpo3VMhY3+SluJkyYoNSoUSPPtuHDhystWrSwZjRFLkvlk06n49ixY3Tt2jXP9q5duxIZGfnQ9xw4cOCB/bt16/bI/UXBzvPfZWRkoNfrKV26tDUiFgsFPc8zZsygbNmyvP7669aOWCwU5Dxv2rSJli1bMmrUKHx9falTpw4zZ87EYDDYInKRVJDz3KZNG44dO5Z7CfvSpUts3ryZZ555xup5S5JHfQ4ePXoUvV5vtXZlisZ8unPnDgaDAV9f3zzbfX19uXnz5kPfc/PmTbP2FwU7z383ceJEAgIC6Ny5szUiFgsFOc/79+9n5cqVREdH2yJisVCQ83zp0iV27dpF//792bx5M+fPn2fUqFHk5OTwwQcf2CJ2kVOQ8/zSSy9x+/Zt2rRpg6Io5OTk8MYbbzBx4kRbRC4xHvU5mJOTw507d/D397dKu1LcmEmj0eR5rijKA9ueZH9hUtDzNnv2bNauXUt4eDjOzs7Wilds5Pc8p6amMmDAAEJDQ/Hx8bFVvGLDnJ9no9FIuXLlWL58OVqtlsaNG3Pjxg3mzJkjxc0/MOc8h4eH8/HHH7N48WKaN2/OhQsXGDNmDP7+/kyZMsUWcUuMh/29PGy7JUlxk08+Pj5otdoHfgtISEh4oCq9z8/Pz6z9RcHO831z585l5syZ7Nixg3r16lkzZpFn7nm+ePEisbGx9OzZM3eb0WgEwN7enrNnzxIcHGzd0EVQQX6e/f39cXBwQKvV5m6rWbMmN2/eRKfT4ejoaNXMRVFBzvOUKVMYOHAgQ4YMAaBu3bqkp6czbNgwJk+ejJ2djNqwhEd9Dtrb21OmTBmrtSt/e/nk6OhI48aNCQsLy7M9LCyMVq1aPfQ9LVu2fGD/7du3P3J/UbDzDDBnzhw+/PBDtm7dSpMmTawds8gz9zzXqFGDkydPEh0dnfv13HPP0aFDB6KjowkMDLRV9CKlID/PrVu35sKFC7nFI8C5c+fw9/eXwuYRCnKeMzIyHihgtFotiulGG6tlLWke9TnYpEkTHBwcrNewVYcrFzP3bzVcuXKlcvr0aWXs2LGKq6urEhsbqyiKogwcODDPyPz9+/crWq1W+eSTT5SYmBjlk08+kVvB88Hc8/zpp58qjo6Oyk8//aTEx8fnfqWmpqr1LRQJ5p7nv5O7pfLH3PMcFxenuLm5KW+++aZy9uxZ5bffflPKlSunfPTRR2p9C0WCued56tSpiru7u7J27Vrl0qVLyvbt25Xg4GClb9++an0LRUJqaqoSFRWlREVFKYAyb948JSoqKveW+4kTJyoDBw7M3f/+reDjxo1TTp8+raxcuVJuBS+MFi1apFSqVElxdHRUGjVqpOzZsyf3tXbt2imvvvpqnv1//PFHpXr16oqDg4NSo0YN5eeff7Zx4qLJnPNcqVIlBXjga+rUqbYPXsSY+/P8v6S4yT9zz3NkZKTSvHlzxcnJSQkKClI+/vhjJScnx8apix5zzrNer1emTZumBAcHK87OzkpgYKAycuRI5d69eyokLzp279790P9v75/bV199VWnXrl2e94SHhysNGzZUHB0dlcqVKytLliyxek6Nokj/mxBCCCGKDxlzI4QQQohiRYobIYQQQhQrUtwIIYQQoliR4kYIIYQQxYoUN0IIIYQoVqS4EUIIIUSxIsWNEEIIIYoVKW6EEEIIUaxIcSOEEE9g9erVeHl5Wb2dypUro9Fo0Gg0JCUlPTbP/f3Gjh1r9VxCFEZS3AhRhC1duhR3d3dycnJyt6WlpeHg4EBISEiefSMiItBoNJw7dy5fx7bVh3ZBTZs2jQYNGti0zcqVK7NgwYI82/r165fvc/qkZsyYQXx8PJ6eno/cp1+/fsTHx9OyZUubZBKiMJLiRogirEOHDqSlpXH06NHcbREREfj5+XHkyBEyMjJyt4eHh1O+fHmqVatm04wGgyHPCteFjaIoeYpDc7m4uFCuXDkLJno0d3d3/Pz80Gg0j83j5+cnK4iLEk2KGyGKsOrVq1O+fHnCw8Nzt4WHh9OrVy+Cg4OJjIzMs71Dhw65z+fNm0fdunVxdXUlMDCQkSNHkpaWlrvv4MGDSU5Ozr3EMW3aNAB0Oh0TJkwgICAAV1dXmjdvnqf9+z0+v/32G7Vq1cLJyYkrV648kP3evXv079+fsmXL4uLiQtWqVVm1alXu6++99x7VqlWjVKlSBAUFMWXKFPR6fW4b06dP5/jx47n5Vq9eTWxsLBqNhujo6NzjJCUlodFocjOGh4ej0WjYtm0bTZo0wcnJiYiICC5evEivXr3w9fXFzc2Npk2bsmPHjtzjtG/fnitXrjBu3LjcNv/3+/1fS5YsITg4GEdHR6pXr84333yT53WNRsOKFSvo3bs3pUqVomrVqmzatOmRf89CCPNIcSNEEde+fXt2796d+3z37t20b9+edu3a5W7X6XQcOHAgT3FjZ2fH559/zqlTp1izZg27du1iwoQJALRq1YoFCxbg4eFBfHw88fHxvPPOOwAMHjyY/fv3s27dOk6cOMGLL75I9+7dOX/+fO6xMzIymDVrFitWrOCPP/54aM/GlClTOH36NFu2bCEmJoYlS5bg4+OT+7q7uzurV6/m9OnTLFy4kNDQUObPnw+YLr28/fbb1K5dOzdfv379zDpvEyZMYNasWcTExFCvXj3S0tJ4+umn2bFjB1FRUXTr1o2ePXsSFxcHwIYNG6hQoULupaH4+PiHHnfjxo2MGTOGt99+m1OnTjF8+HAGDx6c5+8IYPr06fTt25cTJ07w9NNP079/f+7evWvW9yCEeASrrzsuhLCq5cuXK66uroper1dSUlIUe3t75datW8q6deuUVq1aKYqiKHv27FEA5eLFi488zg8//KCUKVMm9/mqVRVfhUsAAAYKSURBVKsUT0/PPPtcuHBB0Wg0yvXr1/Ns79SpkzJp0qTc9wFKdHT0Y3P37NlTGTx4cL6/z9mzZyuNGzfOfT516lSlfv36efa5fPmyAihRUVG52+7du6cAyu7duxVFUZTdu3crgPLf//73H9usVauW8sUXX+Q+r1SpkjJ//vw8+/z9PLVq1UoZOnRonn1efPFF5emnn859Dijvv/9+7vO0tDRFo9EoW7ZseWSWh7X9OO3atVPGjBmT7/2FKE6k50aIIq5Dhw6kp6dz5MgRIiIiqFatGuXKlaNdu3YcOXKE9PR0wsPDqVixIkFBQbnv2717N126dCEgIAB3d3cGDRpEYmIi6enpj2zr999/R1EUqlWrhpubW+7Xnj17uHjxYu5+jo6O1KtX77G533jjDdatW0eDBg2YMGFCnktoAD/99BNt2rTBz88PNzc3pkyZktuLYglNmjTJ8zw9PZ0JEyZQq1YtvLy8cHNz48yZM2a3GRMT8//t3V9IU30cx/G37clYzv7BsAvD6Q6F2J/NCkKpOb3QhPWHooRgLLpZGFTECCkFU+jfVkQ3eaNX0ujCLsoLoTLSiUFBd13muolEkFCw8s+ei3gOHjUf7flX5/m8rrbvzu93vme7+e53vr+N8vJyS6y8vJy3b99aYrPfn5ycHHJzcxkeHl7WuWZ/BtFodFljRezst/86ARH5awzDID8/n97eXkZHRwkEAgBs3LiRwsJCUqkUvb29VFZWmmPS6TS1tbVEo1FaWlrYsGED/f39nDp1yuxrWcjMzAwOh4PXr1/jcDgsr7lcLvOx0+lctOkVYP/+/aTTabq7u3ny5AlVVVXU19cTj8cZHBykrq6O5uZmqqurWbt2LclkkkQiseicK1Z8+76WyWTM2PeuJycnx/I8FovR09NDPB7HMAycTidHjx7l69evi55zIXOvPZPJzIutXLly3pjlNl7P7i1as2bNMrMUsS8VNyI2EAwGef78OaOjo8RiMTMeCATo6elhcHCQkydPmvFXr14xNTVFIpEwC4IHDx5Y5szOzmZ6etoS8/v9TE9PMzw8PG+r+Y9wu91EIhEikQh79+4lFosRj8dJpVIUFBRw6dIl89i5TckL5ed2uwH48OEDfr8fsBYAi+nr6yMSiXD48GHg25b6oaGhPz3nXMXFxfT39xMOh83YwMAAxcXFS8pjOQzD+NvnFLEDFTciNhAMBqmvr2dyctJcuYFvxc3p06f5/PmzpZnY6/UyNTXF3bt3CYVCpFIp7t27Z5nT4/EwPj7O06dP2bFjB6tXr2bz5s2cOHGCcDhMIpHA7/czMjLCs2fP2LZtG7W1tUvOuampiZ07d1JSUsKXL194/PixWQAYhsH79+9JJpPs3r2b7u5uHj58OC+/d+/e8ebNG/Lz88nNzcXpdLJnzx6uXbuGx+NhZGSEy5cvLykfwzDo6uoiFAqRlZVFY2PjvJUUj8fDixcvqKurY9WqVZYG6D/EYjGOHTtGaWkpVVVVPHr0iK6uLsvOKxH5Z6nnRsQGgsEgExMTGIZBXl6eGQ8EAoyNjeH1etm0aZMZ9/l83Lp1i+vXr7N161Y6Ozu5evWqZc6ysjKi0SjHjx/H7XZz48YNADo6OgiHw1y4cIEtW7Zw4MABXr58aZl/KbKzs2loaGD79u3s27cPh8NBMpkE4ODBg5w/f54zZ87g8/kYGBigsbHRMv7IkSPU1NQQDAZxu93cv38fgPb2diYnJ9m1axdnz56ltbV1Sfncvn2b9evXU1ZWRigUorq6mtLSUssxV65cYWhoCK/Xa64SzXXo0CHu3LnDzZs3KSkpoa2tjY6ODioqKpb1/ojIj8vKzL45LSIiPyWPx8O5c+eW/JcKFRUV+Hy+eb+oLPJ/oJUbEZFfxMWLF3G5XHz69Om7x3R2duJyuejr6/sXMxP5uWjlRkTkF5BOp82dX0VFRWYj+FxjY2N8/PgRgHXr1i3YFyRidypuRERExFZ0W0pERERsRcWNiIiI2IqKGxEREbEVFTciIiJiKypuRERExFZU3IiIiIitqLgRERERW1FxIyIiIrbyO3wQZb39ic3NAAAAAElFTkSuQmCC",
      "text/plain": [
       "Figure(PyObject <Figure size 640x480 with 1 Axes>)"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": "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",
      "text/plain": [
       "Figure(PyObject <Figure size 640x480 with 1 Axes>)"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": "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",
      "text/plain": [
       "Figure(PyObject <Figure size 640x480 with 1 Axes>)"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": "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",
      "text/plain": [
       "Figure(PyObject <Figure size 640x480 with 1 Axes>)"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": "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",
      "text/plain": [
       "Figure(PyObject <Figure size 640x480 with 1 Axes>)"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "text/plain": [
       "PyObject <matplotlib.legend.Legend object at 0x0000000004D5C748>"
      ]
     },
     "execution_count": 54,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# define the problem\n",
    "sw0 = 0.15 # initial condition of the experiment\n",
    "sor_hs = 0.25 # high salinity (formation water) residual oil saturation\n",
    "sw_init = 1-sor_hs\n",
    "fluids_hs = FF.oil_water_fluids(mu_water=1e-3, mu_oil=2e-3)\n",
    "fluids_ls = FF.oil_water_fluids(mu_water=1e-3, mu_oil=2e-3)\n",
    "rel_perms_hs = FF.oil_water_rel_perms(krw0=0.4, kro0=0.9, \n",
    "        swc=0.15, sor=sor_hs, nw=2.0, no = 2.0)\n",
    "rel_perms_ls = FF.oil_water_rel_perms(krw0=0.3, kro0=0.95, \n",
    "        swc=0.15, sor=0.15, nw=2.0, no = 2.0)\n",
    "core_flood = FF.core_flooding(u_inj=1.15e-5, pv_inject=4.0, p_back=1e5, sw_init=sw_init, \n",
    "    sw_inj=1.0, rel_perms=rel_perms_hs)\n",
    "core_props = FF.core_properties()\n",
    "wf_res = FF.low_sal_water_flood(core_props, fluids_ls, fluids_hs, rel_perms_hs, \n",
    "        rel_perms_ls, core_flood)\n",
    "FF.visualize(wf_res)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# synthetic experimental data\n",
    "Here I scale the calculated recovery data to the total recovery data for a core initially saturated with oil at a saturation close to the connate water saturation, and secondary flooded with formation water."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 55,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": "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",
      "text/plain": [
       "Figure(PyObject <Figure size 800x500 with 2 Axes>)"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "text/plain": [
       "(Figure(PyObject <Figure size 800x500 with 2 Axes>), PyObject <matplotlib.axes._subplots.AxesSubplot object at 0x000000003BB508D0>, PyObject <matplotlib.axes._subplots.AxesSubplot object at 0x000000003B9F4DA0>)"
      ]
     },
     "execution_count": 55,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "R_exp = (wf_res.recovery_time[:,2].*sor_hs.+(1-sor_hs).-sw0)./(1.0-sw0)\n",
    "t_exp_dp = wf_res.dp_time[:,1]\n",
    "dp_exp = wf_res.dp_time[:,2]\n",
    "t_exp_R = wf_res.recovery_time[:,1]\n",
    "# R_exp = wf_res.recovery_time[:,2]\n",
    "plotyy(t_exp_R, R_exp, t_exp_dp, dp_exp, fig_size = [8,5], x_label=\"time [s]\", y1_label=\"R [-]\", y2_label=\"dP [Pa]\")"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Later, we need to convert the above data back to the tertiary recovery factor, as if the core flooding experiments starts with a core saturated with $S_{or,hs}$ oil saturation."
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# define the objective function"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 56,
   "metadata": {},
   "outputs": [],
   "source": [
    "# struct\n",
    "struct exp_data\n",
    "    t_exp_dp\n",
    "    dp_exp\n",
    "    t_exp_R\n",
    "    R_exp\n",
    "end\n",
    "\n",
    "# convert the recovery data\n",
    "R_conv = (R_exp.*(1-sw0).+sw0.-(1-sor_hs))/sor_hs\n",
    "exp_data1 = exp_data(t_exp_dp, dp_exp, t_exp_R, R_conv);"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 57,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": "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",
      "text/plain": [
       "Figure(PyObject <Figure size 640x480 with 1 Axes>)"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": "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",
      "text/plain": [
       "Figure(PyObject <Figure size 640x480 with 1 Axes>)"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "text/plain": [
       "3.9618511090093786"
      ]
     },
     "execution_count": 57,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "\"\"\"\n",
    "rel_perm_param [krw0, kro0, nw, no, swc, sor]\n",
    "core_props, fluids_ls, fluids_hs, rel_perms_hs, \n",
    "        rel_perms_ls, core_flood\n",
    "\"\"\"\n",
    "function error_calc(rel_perm_param, exp_data, core_props, fluids_ls, fluids_hs, \n",
    "        rel_perms_hs, core_flood; w_p=1.0, w_R=1.0)\n",
    "    rel_perms_ls = FF.oil_water_rel_perms(krw0=rel_perm_param[1], kro0=rel_perm_param[2], \n",
    "    swc=rel_perm_param[5], sor=rel_perm_param[6], nw=rel_perm_param[3], no = rel_perm_param[4])\n",
    "    wf_res = FF.low_sal_water_flood(core_props, fluids_ls, fluids_hs, rel_perms_hs, \n",
    "        rel_perms_ls, core_flood)\n",
    "    dp_calc = Spline1D(wf_res.dp_time[:,1], wf_res.dp_time[:,2], k=1, bc=\"nearest\")\n",
    "    R_calc = Spline1D(wf_res.recovery_time[:,1], wf_res.recovery_time[:,2], k=1, bc=\"nearest\")\n",
    "    error_dp = abs.(dp_calc(exp_data.t_exp_dp) .- exp_data.dp_exp)\n",
    "#     println(error_dp)\n",
    "    error_R = abs.(R_calc(exp_data.t_exp_R) .- exp_data.R_exp)\n",
    "#     println(error_R)\n",
    "    error_dp_norm = w_p.*error_dp./exp_data.dp_exp\n",
    "    error_R_norm = w_R.*error_R #./(exp_data.R_exp+eps()) # to avoid division by a small number\n",
    "    return mean(error_R_norm)+mean(error_dp_norm)\n",
    "end\n",
    "\n",
    "function vis_error(rel_perm_param, exp_data, core_props, fluids_ls, fluids_hs, \n",
    "        rel_perms_hs, core_flood)\n",
    "    rel_perms_ls = FF.oil_water_rel_perms(krw0=rel_perm_param[1], kro0=rel_perm_param[2], \n",
    "    swc=rel_perm_param[5], sor=rel_perm_param[6], nw=rel_perm_param[3], no = rel_perm_param[4])\n",
    "    wf_res = FF.low_sal_water_flood(core_props, fluids_ls, fluids_hs, rel_perms_hs, \n",
    "        rel_perms_ls, core_flood)\n",
    "    figure()\n",
    "    plot(wf_res.dp_time[:,1], wf_res.dp_time[:,2],  exp_data.t_exp_dp, exp_data.dp_exp, \"o\")\n",
    "    xlabel(\"t [s]\")\n",
    "    ylabel(\"dp [Pa]\")\n",
    "    legend([\"Theoretical\", \"Experiment\"])\n",
    "    \n",
    "    figure()\n",
    "    plot(wf_res.recovery_time[:,1], wf_res.recovery_time[:,2], exp_data.t_exp_R, exp_data.R_exp, \"v\")\n",
    "    xlabel(\"t [s]\")\n",
    "    ylabel(\"R [-]\")\n",
    "    legend([\"Theoretical\", \"Experiment\"])\n",
    "    \n",
    "end\n",
    "\n",
    "# test\n",
    "x_init = [0.109681, 0.201297, 3.96653, 3.0, 0.19, 0.1]\n",
    "\n",
    "vis_error(x_init, exp_data1, core_props, fluids_ls, fluids_hs, rel_perms_hs, core_flood)\n",
    "error_calc(x_init, exp_data1, core_props, fluids_ls, fluids_hs, rel_perms_hs, core_flood)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# define the objective function and gradients and weight factors"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 58,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "0.847348832234076"
      ]
     },
     "execution_count": 58,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# weight factors:\n",
    "w_p = ones(length(exp_data1.dp_exp))\n",
    "temp_val, ind_max = findmax(exp_data1.dp_exp)\n",
    "w_p[ind_max-1:ind_max+2] .= 10\n",
    "w_p[end:end-5] .= 10\n",
    "w_p[1] = 10\n",
    "w_R = ones(length(exp_data1.R_exp))\n",
    "w_R[20:25] .= 10\n",
    "w_R[end:end-5] .= 10\n",
    "\n",
    "\n",
    "function f(x)\n",
    "    f_val = 0.0\n",
    "    try\n",
    "        f_val = error_calc(x, exp_data1, core_props, fluids_ls, fluids_hs, \n",
    "            rel_perms_hs, core_flood, w_p = w_p, w_R = w_R)\n",
    "    catch\n",
    "        f_val = 100.0\n",
    "#         info(\"Objective function did not converge!\")\n",
    "    end\n",
    "    return f_val\n",
    "end\n",
    "\n",
    "    \n",
    "function g(x)\n",
    "    eps1 = 1e-4\n",
    "    f_val = f(x)\n",
    "    g_val = ones(length(x))\n",
    "    try\n",
    "        # g_val = Calculus.gradient(x -> error_calc(x, exp_data1, core_props, fluids, core_flood), x)\n",
    "        for j in eachindex(x)\n",
    "            x2 = copy(x)\n",
    "            x2[j]+=eps1\n",
    "            f_val2 = f(x2)\n",
    "            g_val[j] = (f_val2-f_val)/eps1\n",
    "        end\n",
    "    catch\n",
    "        g_val = ones(length(x))\n",
    "    end\n",
    "    return g_val\n",
    "end\n",
    "\n",
    "function obj_fun(param, grad)\n",
    "    if length(grad)>0\n",
    "      grad[:] = g(param)\n",
    "    end\n",
    "    \n",
    "    obj_fun_val = f(param)\n",
    "    if isnan(obj_fun_val) || isinf(obj_fun_val)\n",
    "        obj_fun_val = 100.0\n",
    "    end\n",
    "    return obj_fun_val\n",
    "end\n",
    "\n",
    "# test\n",
    "grad_x = zeros(6)\n",
    "obj_fun([1.0, 0.8, 3, 4, 0.1, 0.1], grad_x)\n",
    "\n",
    "f([1.0, 0.8, 2, 2, 0.1, 0.1])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 59,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Starting optimization with optimizer DiffEvoOpt{FitPopulation{Float64},RadiusLimitedSelector,BlackBoxOptim.AdaptiveDiffEvoRandBin{3},RandomBound{ContinuousRectSearchSpace}}\n",
      "0.00 secs, 0 evals, 0 steps\n",
      "0.51 secs, 20 evals, 10 steps, improv/step: 0.700 (last = 0.7000), fitness=0.130354101\n",
      "1.06 secs, 49 evals, 27 steps, improv/step: 0.519 (last = 0.4118), fitness=0.130354101\n",
      "1.61 secs, 77 evals, 44 steps, improv/step: 0.523 (last = 0.5294), fitness=0.130354101\n",
      "2.11 secs, 109 evals, 64 steps, improv/step: 0.516 (last = 0.5000), fitness=0.123901856\n",
      "2.62 secs, 136 evals, 82 steps, improv/step: 0.537 (last = 0.6111), fitness=0.123901856\n",
      "3.16 secs, 164 evals, 102 steps, improv/step: 0.520 (last = 0.4500), fitness=0.123901856\n",
      "3.71 secs, 189 evals, 119 steps, improv/step: 0.555 (last = 0.7647), fitness=0.123901856\n",
      "4.23 secs, 215 evals, 140 steps, improv/step: 0.529 (last = 0.3810), fitness=0.123901856\n",
      "4.76 secs, 242 evals, 163 steps, improv/step: 0.497 (last = 0.3043), fitness=0.084346110\n",
      "5.28 secs, 264 evals, 180 steps, improv/step: 0.478 (last = 0.2941), fitness=0.084346110\n",
      "5.80 secs, 300 evals, 212 steps, improv/step: 0.476 (last = 0.4688), fitness=0.084346110\n",
      "6.31 secs, 334 evals, 241 steps, improv/step: 0.477 (last = 0.4828), fitness=0.084346110\n",
      "6.81 secs, 356 evals, 260 steps, improv/step: 0.465 (last = 0.3158), fitness=0.084346110\n",
      "7.32 secs, 387 evals, 289 steps, improv/step: 0.467 (last = 0.4828), fitness=0.084346110\n",
      "7.82 secs, 422 evals, 322 steps, improv/step: 0.447 (last = 0.2727), fitness=0.059795116\n",
      "8.33 secs, 458 evals, 356 steps, improv/step: 0.435 (last = 0.3235), fitness=0.059795116\n",
      "8.85 secs, 495 evals, 391 steps, improv/step: 0.417 (last = 0.2286), fitness=0.059795116\n",
      "9.36 secs, 516 evals, 409 steps, improv/step: 0.411 (last = 0.2778), fitness=0.059795116\n",
      "9.90 secs, 540 evals, 431 steps, improv/step: 0.406 (last = 0.3182), fitness=0.059795116\n",
      "10.46 secs, 556 evals, 446 steps, improv/step: 0.404 (last = 0.3333), fitness=0.059795116\n",
      "10.96 secs, 575 evals, 464 steps, improv/step: 0.399 (last = 0.2778), fitness=0.059795116\n",
      "11.47 secs, 600 evals, 488 steps, improv/step: 0.393 (last = 0.2917), fitness=0.059795116\n",
      "11.98 secs, 629 evals, 517 steps, improv/step: 0.395 (last = 0.4138), fitness=0.059795116\n",
      "12.49 secs, 666 evals, 552 steps, improv/step: 0.388 (last = 0.2857), fitness=0.059795116\n",
      "13.00 secs, 702 evals, 587 steps, improv/step: 0.385 (last = 0.3429), fitness=0.059795116\n",
      "13.51 secs, 739 evals, 623 steps, improv/step: 0.376 (last = 0.2222), fitness=0.059795116\n",
      "14.03 secs, 770 evals, 653 steps, improv/step: 0.372 (last = 0.3000), fitness=0.059795116\n",
      "14.55 secs, 793 evals, 675 steps, improv/step: 0.370 (last = 0.3182), fitness=0.059795116\n",
      "15.06 secs, 829 evals, 710 steps, improv/step: 0.359 (last = 0.1429), fitness=0.059795116\n",
      "15.57 secs, 859 evals, 737 steps, improv/step: 0.351 (last = 0.1481), fitness=0.059795116\n",
      "16.08 secs, 889 evals, 766 steps, improv/step: 0.345 (last = 0.1724), fitness=0.059795116\n",
      "16.58 secs, 927 evals, 803 steps, improv/step: 0.337 (last = 0.1892), fitness=0.059795116\n",
      "17.08 secs, 964 evals, 839 steps, improv/step: 0.334 (last = 0.2500), fitness=0.059795116\n",
      "17.60 secs, 1001 evals, 875 steps, improv/step: 0.331 (last = 0.2778), fitness=0.059795116\n",
      "18.11 secs, 1038 evals, 910 steps, improv/step: 0.323 (last = 0.1143), fitness=0.059795116\n",
      "18.61 secs, 1076 evals, 947 steps, improv/step: 0.320 (last = 0.2432), fitness=0.059795116\n",
      "19.12 secs, 1113 evals, 984 steps, improv/step: 0.314 (last = 0.1622), fitness=0.055646045\n",
      "19.63 secs, 1138 evals, 1009 steps, improv/step: 0.311 (last = 0.2000), fitness=0.055646045\n",
      "20.14 secs, 1174 evals, 1043 steps, improv/step: 0.311 (last = 0.2941), fitness=0.055646045\n",
      "20.66 secs, 1212 evals, 1080 steps, improv/step: 0.306 (last = 0.1622), fitness=0.055646045\n",
      "21.17 secs, 1252 evals, 1119 steps, improv/step: 0.300 (last = 0.1538), fitness=0.055646045\n",
      "21.67 secs, 1288 evals, 1154 steps, improv/step: 0.298 (last = 0.2286), fitness=0.055646045\n",
      "22.18 secs, 1323 evals, 1188 steps, improv/step: 0.297 (last = 0.2647), fitness=0.055646045\n",
      "22.70 secs, 1352 evals, 1217 steps, improv/step: 0.296 (last = 0.2414), fitness=0.055646045\n",
      "23.23 secs, 1379 evals, 1244 steps, improv/step: 0.292 (last = 0.1111), fitness=0.055646045\n",
      "23.74 secs, 1409 evals, 1271 steps, improv/step: 0.293 (last = 0.3704), fitness=0.055646045\n",
      "24.25 secs, 1446 evals, 1306 steps, improv/step: 0.293 (last = 0.2857), fitness=0.055646045\n",
      "24.77 secs, 1477 evals, 1335 steps, improv/step: 0.291 (last = 0.2069), fitness=0.055646045\n",
      "25.28 secs, 1514 evals, 1369 steps, improv/step: 0.290 (last = 0.2353), fitness=0.055646045\n",
      "25.80 secs, 1547 evals, 1402 steps, improv/step: 0.287 (last = 0.1818), fitness=0.055646045\n",
      "26.30 secs, 1584 evals, 1437 steps, improv/step: 0.288 (last = 0.3143), fitness=0.055646045\n",
      "26.80 secs, 1621 evals, 1474 steps, improv/step: 0.284 (last = 0.1081), fitness=0.055646045\n",
      "27.31 secs, 1646 evals, 1499 steps, improv/step: 0.281 (last = 0.1200), fitness=0.055646045\n",
      "27.82 secs, 1674 evals, 1527 steps, improv/step: 0.280 (last = 0.2143), fitness=0.031175328\n",
      "28.32 secs, 1713 evals, 1566 steps, improv/step: 0.277 (last = 0.1795), fitness=0.031175328\n",
      "28.84 secs, 1752 evals, 1605 steps, improv/step: 0.273 (last = 0.1026), fitness=0.031175328\n",
      "29.34 secs, 1788 evals, 1641 steps, improv/step: 0.269 (last = 0.1111), fitness=0.031175328\n",
      "29.87 secs, 1816 evals, 1669 steps, improv/step: 0.267 (last = 0.1429), fitness=0.031175328\n",
      "30.37 secs, 1850 evals, 1702 steps, improv/step: 0.266 (last = 0.1818), fitness=0.027441003\n",
      "30.88 secs, 1888 evals, 1740 steps, improv/step: 0.264 (last = 0.2105), fitness=0.027441003\n",
      "31.38 secs, 1927 evals, 1779 steps, improv/step: 0.263 (last = 0.2051), fitness=0.027441003\n",
      "31.90 secs, 1953 evals, 1803 steps, improv/step: 0.262 (last = 0.1667), fitness=0.027441003\n",
      "32.41 secs, 1992 evals, 1842 steps, improv/step: 0.259 (last = 0.1282), fitness=0.027441003\n",
      "32.91 secs, 2017 evals, 1866 steps, improv/step: 0.257 (last = 0.0833), fitness=0.027441003\n",
      "33.43 secs, 2045 evals, 1894 steps, improv/step: 0.255 (last = 0.1429), fitness=0.027441003\n",
      "33.94 secs, 2073 evals, 1921 steps, improv/step: 0.254 (last = 0.1852), fitness=0.027441003\n",
      "34.46 secs, 2098 evals, 1946 steps, improv/step: 0.253 (last = 0.2000), fitness=0.027441003\n",
      "34.97 secs, 2133 evals, 1980 steps, improv/step: 0.252 (last = 0.1765), fitness=0.027441003\n",
      "35.47 secs, 2159 evals, 2006 steps, improv/step: 0.251 (last = 0.1538), fitness=0.027441003\n",
      "35.99 secs, 2189 evals, 2036 steps, improv/step: 0.249 (last = 0.1333), fitness=0.027441003\n",
      "36.49 secs, 2225 evals, 2069 steps, improv/step: 0.248 (last = 0.2121), fitness=0.023619697\n",
      "37.01 secs, 2262 evals, 2104 steps, improv/step: 0.248 (last = 0.2286), fitness=0.023619697\n",
      "37.51 secs, 2295 evals, 2137 steps, improv/step: 0.247 (last = 0.1818), fitness=0.023619697\n",
      "38.01 secs, 2333 evals, 2175 steps, improv/step: 0.243 (last = 0.0000), fitness=0.023619697\n",
      "38.52 secs, 2368 evals, 2210 steps, improv/step: 0.240 (last = 0.0571), fitness=0.023619697\n",
      "39.04 secs, 2396 evals, 2238 steps, improv/step: 0.238 (last = 0.1071), fitness=0.023619697\n",
      "39.57 secs, 2421 evals, 2262 steps, improv/step: 0.239 (last = 0.3333), fitness=0.023619697\n",
      "40.08 secs, 2451 evals, 2291 steps, improv/step: 0.239 (last = 0.2414), fitness=0.023619697\n",
      "40.58 secs, 2487 evals, 2326 steps, improv/step: 0.237 (last = 0.1143), fitness=0.023619697\n",
      "41.08 secs, 2525 evals, 2362 steps, improv/step: 0.236 (last = 0.1389), fitness=0.023619697\n",
      "41.59 secs, 2552 evals, 2387 steps, improv/step: 0.236 (last = 0.2400), fitness=0.023619697\n",
      "42.09 secs, 2588 evals, 2422 steps, improv/step: 0.236 (last = 0.2571), fitness=0.023619697\n",
      "42.60 secs, 2625 evals, 2458 steps, improv/step: 0.234 (last = 0.1111), fitness=0.023619697\n",
      "43.10 secs, 2664 evals, 2496 steps, improv/step: 0.233 (last = 0.1316), fitness=0.023619697\n",
      "43.61 secs, 2689 evals, 2521 steps, improv/step: 0.232 (last = 0.2000), fitness=0.023619697\n",
      "44.12 secs, 2722 evals, 2553 steps, improv/step: 0.231 (last = 0.1250), fitness=0.023619697\n",
      "44.62 secs, 2748 evals, 2579 steps, improv/step: 0.230 (last = 0.1154), fitness=0.023619697\n",
      "45.14 secs, 2786 evals, 2616 steps, improv/step: 0.229 (last = 0.1351), fitness=0.023619697\n",
      "45.64 secs, 2811 evals, 2641 steps, improv/step: 0.227 (last = 0.0800), fitness=0.023619697\n",
      "46.15 secs, 2847 evals, 2677 steps, improv/step: 0.226 (last = 0.1667), fitness=0.023619697\n",
      "46.66 secs, 2873 evals, 2702 steps, improv/step: 0.226 (last = 0.1600), fitness=0.023619697\n",
      "47.16 secs, 2905 evals, 2733 steps, improv/step: 0.224 (last = 0.0968), fitness=0.022179115\n",
      "47.67 secs, 2945 evals, 2773 steps, improv/step: 0.224 (last = 0.2000), fitness=0.022179115\n",
      "48.19 secs, 2976 evals, 2804 steps, improv/step: 0.224 (last = 0.1935), fitness=0.020426512\n",
      "48.76 secs, 3004 evals, 2832 steps, improv/step: 0.222 (last = 0.1071), fitness=0.019818156\n",
      "49.27 secs, 3033 evals, 2861 steps, improv/step: 0.222 (last = 0.1379), fitness=0.017268805\n",
      "49.78 secs, 3067 evals, 2895 steps, improv/step: 0.221 (last = 0.2059), fitness=0.017268805\n",
      "50.28 secs, 3105 evals, 2932 steps, improv/step: 0.220 (last = 0.1351), fitness=0.017268805\n",
      "50.79 secs, 3144 evals, 2969 steps, improv/step: 0.220 (last = 0.1622), fitness=0.017268805\n",
      "51.30 secs, 3183 evals, 3008 steps, improv/step: 0.218 (last = 0.1282), fitness=0.017268805\n",
      "51.82 secs, 3212 evals, 3037 steps, improv/step: 0.217 (last = 0.1034), fitness=0.017268805\n",
      "52.33 secs, 3244 evals, 3068 steps, improv/step: 0.217 (last = 0.2258), fitness=0.017268805\n",
      "52.84 secs, 3267 evals, 3090 steps, improv/step: 0.217 (last = 0.1364), fitness=0.017268805\n",
      "53.34 secs, 3304 evals, 3127 steps, improv/step: 0.217 (last = 0.2162), fitness=0.017268805\n",
      "53.86 secs, 3343 evals, 3164 steps, improv/step: 0.217 (last = 0.2432), fitness=0.010824736\n",
      "54.37 secs, 3369 evals, 3190 steps, improv/step: 0.216 (last = 0.0385), fitness=0.010824736\n",
      "54.90 secs, 3402 evals, 3223 steps, improv/step: 0.215 (last = 0.1515), fitness=0.006282297\n",
      "55.41 secs, 3428 evals, 3249 steps, improv/step: 0.215 (last = 0.2308), fitness=0.006282297\n",
      "55.92 secs, 3464 evals, 3282 steps, improv/step: 0.215 (last = 0.2121), fitness=0.006282297\n",
      "56.43 secs, 3503 evals, 3321 steps, improv/step: 0.214 (last = 0.1026), fitness=0.006282297\n",
      "56.94 secs, 3537 evals, 3353 steps, improv/step: 0.214 (last = 0.2188), fitness=0.006282297\n",
      "57.45 secs, 3567 evals, 3382 steps, improv/step: 0.213 (last = 0.1379), fitness=0.006282297\n",
      "57.95 secs, 3589 evals, 3404 steps, improv/step: 0.213 (last = 0.2273), fitness=0.006282297\n",
      "58.46 secs, 3622 evals, 3437 steps, improv/step: 0.212 (last = 0.1212), fitness=0.006282297\n",
      "58.96 secs, 3648 evals, 3463 steps, improv/step: 0.211 (last = 0.0769), fitness=0.006282297\n",
      "59.46 secs, 3682 evals, 3493 steps, improv/step: 0.212 (last = 0.3000), fitness=0.006282297\n",
      "59.97 secs, 3715 evals, 3524 steps, improv/step: 0.212 (last = 0.1613), fitness=0.006282297\n",
      "60.48 secs, 3743 evals, 3551 steps, improv/step: 0.212 (last = 0.2593), fitness=0.006282297\n",
      "60.99 secs, 3770 evals, 3578 steps, improv/step: 0.211 (last = 0.0741), fitness=0.006282297\n",
      "61.51 secs, 3801 evals, 3608 steps, improv/step: 0.211 (last = 0.2000), fitness=0.006282297\n",
      "62.02 secs, 3825 evals, 3632 steps, improv/step: 0.211 (last = 0.1667), fitness=0.006282297\n",
      "62.54 secs, 3852 evals, 3658 steps, improv/step: 0.211 (last = 0.2308), fitness=0.006282297\n",
      "63.05 secs, 3891 evals, 3697 steps, improv/step: 0.210 (last = 0.1795), fitness=0.006282297\n",
      "63.55 secs, 3916 evals, 3721 steps, improv/step: 0.211 (last = 0.2917), fitness=0.006282297\n",
      "64.08 secs, 3929 evals, 3734 steps, improv/step: 0.210 (last = 0.0769), fitness=0.006282297\n",
      "64.58 secs, 3964 evals, 3768 steps, improv/step: 0.210 (last = 0.1765), fitness=0.006282297\n",
      "65.09 secs, 4003 evals, 3807 steps, improv/step: 0.209 (last = 0.1282), fitness=0.006282297\n",
      "65.61 secs, 4037 evals, 3841 steps, improv/step: 0.208 (last = 0.0882), fitness=0.006282297\n",
      "66.12 secs, 4066 evals, 3870 steps, improv/step: 0.207 (last = 0.0690), fitness=0.006282297\n",
      "66.63 secs, 4091 evals, 3895 steps, improv/step: 0.207 (last = 0.1600), fitness=0.006282297\n",
      "67.15 secs, 4108 evals, 3912 steps, improv/step: 0.207 (last = 0.1176), fitness=0.006282297\n",
      "67.69 secs, 4126 evals, 3930 steps, improv/step: 0.207 (last = 0.2222), fitness=0.006282297\n",
      "68.20 secs, 4142 evals, 3946 steps, improv/step: 0.206 (last = 0.0625), fitness=0.006282297\n",
      "68.72 secs, 4155 evals, 3959 steps, improv/step: 0.206 (last = 0.2308), fitness=0.006282297\n",
      "69.25 secs, 4170 evals, 3974 steps, improv/step: 0.206 (last = 0.2667), fitness=0.006282297\n",
      "69.79 secs, 4183 evals, 3987 steps, improv/step: 0.206 (last = 0.2308), fitness=0.006282297\n",
      "70.32 secs, 4196 evals, 3999 steps, improv/step: 0.207 (last = 0.3333), fitness=0.006282297\n",
      "70.83 secs, 4207 evals, 4009 steps, improv/step: 0.207 (last = 0.1000), fitness=0.006282297\n",
      "71.34 secs, 4219 evals, 4021 steps, improv/step: 0.207 (last = 0.2500), fitness=0.006282297\n",
      "71.85 secs, 4231 evals, 4033 steps, improv/step: 0.206 (last = 0.0833), fitness=0.006282297\n",
      "72.36 secs, 4246 evals, 4048 steps, improv/step: 0.206 (last = 0.2000), fitness=0.006282297\n",
      "72.88 secs, 4257 evals, 4059 steps, improv/step: 0.206 (last = 0.1818), fitness=0.006282297\n",
      "73.41 secs, 4267 evals, 4069 steps, improv/step: 0.206 (last = 0.3000), fitness=0.006282297\n",
      "73.95 secs, 4277 evals, 4079 steps, improv/step: 0.206 (last = 0.0000), fitness=0.006282297\n",
      "74.45 secs, 4285 evals, 4087 steps, improv/step: 0.206 (last = 0.0000), fitness=0.006282297\n",
      "74.95 secs, 4293 evals, 4094 steps, improv/step: 0.205 (last = 0.1429), fitness=0.006282297\n",
      "75.55 secs, 4304 evals, 4103 steps, improv/step: 0.206 (last = 0.4444), fitness=0.006282297\n",
      "76.09 secs, 4315 evals, 4113 steps, improv/step: 0.206 (last = 0.3000), fitness=0.006282297\n",
      "76.66 secs, 4327 evals, 4125 steps, improv/step: 0.206 (last = 0.0833), fitness=0.006282297\n",
      "77.17 secs, 4337 evals, 4135 steps, improv/step: 0.206 (last = 0.2000), fitness=0.006282297\n",
      "77.69 secs, 4347 evals, 4144 steps, improv/step: 0.206 (last = 0.3333), fitness=0.006165264\n",
      "78.25 secs, 4359 evals, 4155 steps, improv/step: 0.206 (last = 0.3636), fitness=0.006165264\n",
      "78.78 secs, 4370 evals, 4166 steps, improv/step: 0.206 (last = 0.1818), fitness=0.006165264\n",
      "79.30 secs, 4385 evals, 4181 steps, improv/step: 0.206 (last = 0.0667), fitness=0.006165264\n",
      "79.81 secs, 4409 evals, 4205 steps, improv/step: 0.205 (last = 0.0833), fitness=0.006165264\n",
      "80.32 secs, 4446 evals, 4242 steps, improv/step: 0.204 (last = 0.0541), fitness=0.006165264\n",
      "80.84 secs, 4473 evals, 4269 steps, improv/step: 0.203 (last = 0.0741), fitness=0.006165264\n",
      "81.35 secs, 4504 evals, 4300 steps, improv/step: 0.203 (last = 0.1935), fitness=0.006165264\n",
      "81.86 secs, 4529 evals, 4325 steps, improv/step: 0.203 (last = 0.1200), fitness=0.006165264\n",
      "82.37 secs, 4554 evals, 4350 steps, improv/step: 0.203 (last = 0.2000), fitness=0.006165264\n",
      "82.88 secs, 4579 evals, 4375 steps, improv/step: 0.202 (last = 0.1200), fitness=0.006165264\n",
      "83.39 secs, 4613 evals, 4409 steps, improv/step: 0.202 (last = 0.1765), fitness=0.006133581\n",
      "83.91 secs, 4651 evals, 4446 steps, improv/step: 0.201 (last = 0.1351), fitness=0.006133581\n",
      "84.41 secs, 4691 evals, 4486 steps, improv/step: 0.200 (last = 0.1000), fitness=0.006133581\n",
      "84.92 secs, 4731 evals, 4525 steps, improv/step: 0.201 (last = 0.2564), fitness=0.006133581\n",
      "85.42 secs, 4756 evals, 4550 steps, improv/step: 0.201 (last = 0.1600), fitness=0.005812309\n",
      "85.94 secs, 4790 evals, 4583 steps, improv/step: 0.201 (last = 0.2121), fitness=0.005812309\n",
      "86.45 secs, 4822 evals, 4615 steps, improv/step: 0.200 (last = 0.0313), fitness=0.005812309\n",
      "86.96 secs, 4854 evals, 4645 steps, improv/step: 0.199 (last = 0.1667), fitness=0.005715130\n",
      "87.47 secs, 4892 evals, 4683 steps, improv/step: 0.199 (last = 0.1579), fitness=0.005715130\n",
      "87.99 secs, 4912 evals, 4703 steps, improv/step: 0.200 (last = 0.3500), fitness=0.005715130\n",
      "88.49 secs, 4950 evals, 4741 steps, improv/step: 0.198 (last = 0.0526), fitness=0.005715130\n",
      "88.99 secs, 4988 evals, 4778 steps, improv/step: 0.197 (last = 0.0541), fitness=0.005715130\n",
      "89.52 secs, 5022 evals, 4812 steps, improv/step: 0.197 (last = 0.0882), fitness=0.003842075\n",
      "90.02 secs, 5053 evals, 4843 steps, improv/step: 0.196 (last = 0.0323), fitness=0.003842075\n",
      "90.53 secs, 5080 evals, 4870 steps, improv/step: 0.195 (last = 0.0741), fitness=0.003842075\n",
      "91.03 secs, 5110 evals, 4900 steps, improv/step: 0.195 (last = 0.2000), fitness=0.003222240\n",
      "91.54 secs, 5142 evals, 4932 steps, improv/step: 0.194 (last = 0.0938), fitness=0.003222240\n",
      "92.05 secs, 5167 evals, 4957 steps, improv/step: 0.193 (last = 0.0400), fitness=0.003222240\n",
      "92.55 secs, 5203 evals, 4993 steps, improv/step: 0.193 (last = 0.1944), fitness=0.003222240\n",
      "93.06 secs, 5240 evals, 5029 steps, improv/step: 0.194 (last = 0.3056), fitness=0.003222240\n",
      "93.57 secs, 5280 evals, 5069 steps, improv/step: 0.194 (last = 0.1000), fitness=0.003222240\n",
      "94.08 secs, 5321 evals, 5110 steps, improv/step: 0.193 (last = 0.1220), fitness=0.003222240\n",
      "94.59 secs, 5361 evals, 5150 steps, improv/step: 0.193 (last = 0.1500), fitness=0.003222240\n",
      "95.09 secs, 5402 evals, 5191 steps, improv/step: 0.192 (last = 0.0976), fitness=0.003222240\n",
      "95.60 secs, 5441 evals, 5230 steps, improv/step: 0.191 (last = 0.1282), fitness=0.003222240\n",
      "96.10 secs, 5481 evals, 5270 steps, improv/step: 0.191 (last = 0.1750), fitness=0.002443829\n",
      "96.60 secs, 5521 evals, 5308 steps, improv/step: 0.191 (last = 0.1842), fitness=0.002443829\n",
      "97.11 secs, 5560 evals, 5347 steps, improv/step: 0.191 (last = 0.1795), fitness=0.002443829\n",
      "97.62 secs, 5596 evals, 5382 steps, improv/step: 0.192 (last = 0.3429), fitness=0.002443829\n",
      "98.13 secs, 5636 evals, 5419 steps, improv/step: 0.192 (last = 0.1622), fitness=0.002443829\n",
      "98.64 secs, 5676 evals, 5459 steps, improv/step: 0.191 (last = 0.0750), fitness=0.002443829\n",
      "99.14 secs, 5712 evals, 5494 steps, improv/step: 0.191 (last = 0.1714), fitness=0.002443829\n",
      "99.64 secs, 5750 evals, 5532 steps, improv/step: 0.191 (last = 0.1842), fitness=0.001803434\n",
      "100.15 secs, 5788 evals, 5569 steps, improv/step: 0.191 (last = 0.1351), fitness=0.001803434\n",
      "100.65 secs, 5825 evals, 5605 steps, improv/step: 0.190 (last = 0.1389), fitness=0.001803434\n",
      "101.16 secs, 5863 evals, 5641 steps, improv/step: 0.191 (last = 0.2500), fitness=0.001803434\n",
      "101.66 secs, 5902 evals, 5680 steps, improv/step: 0.190 (last = 0.1026), fitness=0.001803434\n",
      "102.17 secs, 5937 evals, 5714 steps, improv/step: 0.190 (last = 0.2059), fitness=0.001803434\n",
      "102.68 secs, 5972 evals, 5748 steps, improv/step: 0.190 (last = 0.1765), fitness=0.001803434\n",
      "103.18 secs, 6012 evals, 5788 steps, improv/step: 0.190 (last = 0.2000), fitness=0.001803434\n",
      "103.69 secs, 6051 evals, 5826 steps, improv/step: 0.190 (last = 0.1316), fitness=0.001803434\n",
      "104.19 secs, 6088 evals, 5862 steps, improv/step: 0.189 (last = 0.1111), fitness=0.001803434\n",
      "104.70 secs, 6127 evals, 5901 steps, improv/step: 0.189 (last = 0.1795), fitness=0.001803434\n",
      "105.21 secs, 6167 evals, 5940 steps, improv/step: 0.189 (last = 0.1538), fitness=0.001803434\n",
      "105.71 secs, 6205 evals, 5977 steps, improv/step: 0.188 (last = 0.1081), fitness=0.001803434\n",
      "106.22 secs, 6244 evals, 6015 steps, improv/step: 0.188 (last = 0.0789), fitness=0.001803434\n",
      "106.72 secs, 6274 evals, 6045 steps, improv/step: 0.187 (last = 0.1000), fitness=0.001803434\n",
      "107.23 secs, 6292 evals, 6063 steps, improv/step: 0.187 (last = 0.0000), fitness=0.001803434\n",
      "107.74 secs, 6327 evals, 6098 steps, improv/step: 0.187 (last = 0.1714), fitness=0.001137763\n",
      "108.27 secs, 6363 evals, 6134 steps, improv/step: 0.187 (last = 0.1667), fitness=0.001137763\n",
      "108.77 secs, 6399 evals, 6170 steps, improv/step: 0.186 (last = 0.1667), fitness=0.001137763\n",
      "109.28 secs, 6439 evals, 6210 steps, improv/step: 0.187 (last = 0.2500), fitness=0.001137763\n",
      "109.79 secs, 6476 evals, 6247 steps, improv/step: 0.186 (last = 0.1081), fitness=0.001137763\n",
      "110.29 secs, 6516 evals, 6287 steps, improv/step: 0.186 (last = 0.0750), fitness=0.001137763\n",
      "110.80 secs, 6555 evals, 6326 steps, improv/step: 0.185 (last = 0.1026), fitness=0.001137763\n",
      "111.32 secs, 6593 evals, 6364 steps, improv/step: 0.185 (last = 0.1842), fitness=0.001137763\n",
      "111.82 secs, 6631 evals, 6402 steps, improv/step: 0.185 (last = 0.1316), fitness=0.001137763\n",
      "112.32 secs, 6666 evals, 6437 steps, improv/step: 0.185 (last = 0.2286), fitness=0.001137763\n",
      "112.84 secs, 6705 evals, 6476 steps, improv/step: 0.185 (last = 0.1282), fitness=0.001137763\n",
      "113.35 secs, 6744 evals, 6514 steps, improv/step: 0.185 (last = 0.2368), fitness=0.001137763\n",
      "113.85 secs, 6784 evals, 6553 steps, improv/step: 0.185 (last = 0.1795), fitness=0.001137763\n",
      "114.37 secs, 6823 evals, 6592 steps, improv/step: 0.185 (last = 0.1282), fitness=0.001137763\n",
      "114.88 secs, 6862 evals, 6631 steps, improv/step: 0.185 (last = 0.2308), fitness=0.001036962\n",
      "115.38 secs, 6898 evals, 6667 steps, improv/step: 0.184 (last = 0.0556), fitness=0.001036962\n",
      "115.88 secs, 6936 evals, 6705 steps, improv/step: 0.184 (last = 0.0789), fitness=0.001036962\n",
      "116.39 secs, 6976 evals, 6745 steps, improv/step: 0.184 (last = 0.1750), fitness=0.001036962\n",
      "116.89 secs, 7016 evals, 6785 steps, improv/step: 0.184 (last = 0.2000), fitness=0.001036962\n",
      "117.40 secs, 7055 evals, 6824 steps, improv/step: 0.183 (last = 0.0513), fitness=0.001036962\n",
      "117.91 secs, 7096 evals, 6865 steps, improv/step: 0.183 (last = 0.1220), fitness=0.001011167\n",
      "118.42 secs, 7136 evals, 6905 steps, improv/step: 0.182 (last = 0.1500), fitness=0.001011167\n",
      "118.93 secs, 7175 evals, 6944 steps, improv/step: 0.182 (last = 0.0769), fitness=0.001011167\n",
      "119.43 secs, 7212 evals, 6981 steps, improv/step: 0.181 (last = 0.1081), fitness=0.000511087\n",
      "119.93 secs, 7251 evals, 7020 steps, improv/step: 0.181 (last = 0.0513), fitness=0.000511087\n",
      "120.43 secs, 7276 evals, 7045 steps, improv/step: 0.180 (last = 0.0800), fitness=0.000511087\n",
      "120.96 secs, 7309 evals, 7078 steps, improv/step: 0.179 (last = 0.0000), fitness=0.000511087\n",
      "121.46 secs, 7339 evals, 7108 steps, improv/step: 0.179 (last = 0.0333), fitness=0.000511087\n",
      "121.96 secs, 7375 evals, 7144 steps, improv/step: 0.178 (last = 0.0833), fitness=0.000511087\n",
      "122.47 secs, 7414 evals, 7183 steps, improv/step: 0.178 (last = 0.1795), fitness=0.000511087\n",
      "122.98 secs, 7455 evals, 7224 steps, improv/step: 0.178 (last = 0.1463), fitness=0.000511087\n",
      "123.49 secs, 7495 evals, 7264 steps, improv/step: 0.178 (last = 0.1750), fitness=0.000511087\n",
      "123.99 secs, 7533 evals, 7302 steps, improv/step: 0.178 (last = 0.2105), fitness=0.000511087\n",
      "124.50 secs, 7573 evals, 7342 steps, improv/step: 0.178 (last = 0.0750), fitness=0.000511087\n",
      "125.01 secs, 7613 evals, 7382 steps, improv/step: 0.177 (last = 0.0750), fitness=0.000511087\n",
      "125.51 secs, 7651 evals, 7420 steps, improv/step: 0.177 (last = 0.0789), fitness=0.000511087\n",
      "126.02 secs, 7688 evals, 7457 steps, improv/step: 0.176 (last = 0.0811), fitness=0.000511087\n",
      "126.53 secs, 7715 evals, 7484 steps, improv/step: 0.176 (last = 0.0370), fitness=0.000511087\n",
      "127.04 secs, 7746 evals, 7515 steps, improv/step: 0.175 (last = 0.0968), fitness=0.000511087\n",
      "127.55 secs, 7771 evals, 7540 steps, improv/step: 0.175 (last = 0.1200), fitness=0.000511087\n",
      "128.05 secs, 7806 evals, 7575 steps, improv/step: 0.175 (last = 0.0571), fitness=0.000511087\n",
      "128.55 secs, 7846 evals, 7615 steps, improv/step: 0.174 (last = 0.1000), fitness=0.000475263\n",
      "129.07 secs, 7881 evals, 7650 steps, improv/step: 0.174 (last = 0.1143), fitness=0.000475263\n",
      "129.57 secs, 7917 evals, 7686 steps, improv/step: 0.173 (last = 0.0556), fitness=0.000475263\n",
      "130.08 secs, 7956 evals, 7725 steps, improv/step: 0.173 (last = 0.0769), fitness=0.000475263\n",
      "130.58 secs, 7993 evals, 7762 steps, improv/step: 0.173 (last = 0.0811), fitness=0.000475263\n",
      "131.09 secs, 8033 evals, 7802 steps, improv/step: 0.172 (last = 0.0750), fitness=0.000475263\n",
      "131.59 secs, 8070 evals, 7839 steps, improv/step: 0.172 (last = 0.1081), fitness=0.000475263\n",
      "132.10 secs, 8093 evals, 7862 steps, improv/step: 0.172 (last = 0.1739), fitness=0.000422055\n",
      "132.60 secs, 8125 evals, 7894 steps, improv/step: 0.171 (last = 0.0938), fitness=0.000422055\n",
      "133.10 secs, 8163 evals, 7932 steps, improv/step: 0.171 (last = 0.1316), fitness=0.000326960\n",
      "133.62 secs, 8201 evals, 7970 steps, improv/step: 0.171 (last = 0.1053), fitness=0.000326960\n",
      "134.12 secs, 8242 evals, 8011 steps, improv/step: 0.171 (last = 0.1463), fitness=0.000326960\n",
      "134.63 secs, 8281 evals, 8050 steps, improv/step: 0.170 (last = 0.0256), fitness=0.000326960\n",
      "135.14 secs, 8321 evals, 8090 steps, improv/step: 0.170 (last = 0.0750), fitness=0.000326960\n",
      "135.64 secs, 8358 evals, 8127 steps, improv/step: 0.169 (last = 0.0270), fitness=0.000326960\n",
      "136.15 secs, 8395 evals, 8165 steps, improv/step: 0.169 (last = 0.1579), fitness=0.000326960\n",
      "136.66 secs, 8433 evals, 8203 steps, improv/step: 0.169 (last = 0.1053), fitness=0.000326960\n",
      "137.17 secs, 8472 evals, 8242 steps, improv/step: 0.169 (last = 0.2051), fitness=0.000326960\n",
      "137.67 secs, 8510 evals, 8280 steps, improv/step: 0.168 (last = 0.0789), fitness=0.000326960\n",
      "138.18 secs, 8548 evals, 8318 steps, improv/step: 0.168 (last = 0.1053), fitness=0.000326960\n",
      "138.69 secs, 8583 evals, 8353 steps, improv/step: 0.168 (last = 0.0571), fitness=0.000326960\n",
      "139.21 secs, 8613 evals, 8383 steps, improv/step: 0.167 (last = 0.1000), fitness=0.000326960\n",
      "139.72 secs, 8638 evals, 8408 steps, improv/step: 0.168 (last = 0.2400), fitness=0.000326960\n",
      "140.23 secs, 8663 evals, 8433 steps, improv/step: 0.167 (last = 0.1200), fitness=0.000326960\n",
      "140.73 secs, 8700 evals, 8470 steps, improv/step: 0.167 (last = 0.1081), fitness=0.000275498\n",
      "141.24 secs, 8728 evals, 8498 steps, improv/step: 0.167 (last = 0.1071), fitness=0.000275498\n",
      "141.74 secs, 8766 evals, 8536 steps, improv/step: 0.167 (last = 0.0789), fitness=0.000270849\n",
      "142.24 secs, 8806 evals, 8576 steps, improv/step: 0.166 (last = 0.1000), fitness=0.000261780\n",
      "142.75 secs, 8843 evals, 8613 steps, improv/step: 0.166 (last = 0.0541), fitness=0.000261780\n",
      "143.26 secs, 8879 evals, 8649 steps, improv/step: 0.166 (last = 0.1111), fitness=0.000261780\n",
      "143.76 secs, 8916 evals, 8686 steps, improv/step: 0.165 (last = 0.0811), fitness=0.000261780\n",
      "144.27 secs, 8953 evals, 8723 steps, improv/step: 0.165 (last = 0.1622), fitness=0.000261780\n",
      "144.78 secs, 8994 evals, 8764 steps, improv/step: 0.165 (last = 0.0976), fitness=0.000261780\n",
      "145.28 secs, 9031 evals, 8801 steps, improv/step: 0.165 (last = 0.1081), fitness=0.000227520\n",
      "145.79 secs, 9068 evals, 8838 steps, improv/step: 0.165 (last = 0.1892), fitness=0.000227520\n",
      "146.30 secs, 9107 evals, 8877 steps, improv/step: 0.165 (last = 0.1795), fitness=0.000227520\n",
      "146.81 secs, 9146 evals, 8916 steps, improv/step: 0.165 (last = 0.1282), fitness=0.000227520\n",
      "147.33 secs, 9183 evals, 8953 steps, improv/step: 0.165 (last = 0.1351), fitness=0.000227520\n",
      "147.83 secs, 9222 evals, 8992 steps, improv/step: 0.164 (last = 0.1026), fitness=0.000227520\n",
      "148.34 secs, 9257 evals, 9027 steps, improv/step: 0.164 (last = 0.1429), fitness=0.000227520\n",
      "148.85 secs, 9295 evals, 9065 steps, improv/step: 0.164 (last = 0.1842), fitness=0.000227520\n",
      "149.35 secs, 9325 evals, 9095 steps, improv/step: 0.165 (last = 0.2667), fitness=0.000227520\n",
      "149.87 secs, 9343 evals, 9113 steps, improv/step: 0.165 (last = 0.1667), fitness=0.000227520\n",
      "150.38 secs, 9382 evals, 9152 steps, improv/step: 0.165 (last = 0.2051), fitness=0.000227520\n",
      "150.88 secs, 9419 evals, 9189 steps, improv/step: 0.165 (last = 0.1351), fitness=0.000134806\n",
      "151.40 secs, 9459 evals, 9229 steps, improv/step: 0.165 (last = 0.1500), fitness=0.000134806\n",
      "151.90 secs, 9497 evals, 9267 steps, improv/step: 0.165 (last = 0.2105), fitness=0.000134806\n",
      "152.41 secs, 9526 evals, 9296 steps, improv/step: 0.165 (last = 0.1034), fitness=0.000134806\n",
      "152.92 secs, 9558 evals, 9328 steps, improv/step: 0.164 (last = 0.0938), fitness=0.000134806\n",
      "153.44 secs, 9589 evals, 9359 steps, improv/step: 0.164 (last = 0.1613), fitness=0.000134806\n",
      "153.95 secs, 9630 evals, 9400 steps, improv/step: 0.164 (last = 0.0976), fitness=0.000134806\n",
      "154.46 secs, 9670 evals, 9440 steps, improv/step: 0.164 (last = 0.1750), fitness=0.000134806\n",
      "154.96 secs, 9710 evals, 9480 steps, improv/step: 0.164 (last = 0.0750), fitness=0.000134806\n",
      "155.47 secs, 9748 evals, 9518 steps, improv/step: 0.164 (last = 0.1842), fitness=0.000122375\n",
      "155.97 secs, 9788 evals, 9558 steps, improv/step: 0.164 (last = 0.2000), fitness=0.000122375\n",
      "156.48 secs, 9823 evals, 9593 steps, improv/step: 0.164 (last = 0.1429), fitness=0.000122375\n",
      "156.98 secs, 9853 evals, 9623 steps, improv/step: 0.164 (last = 0.1000), fitness=0.000122375\n",
      "157.49 secs, 9889 evals, 9659 steps, improv/step: 0.164 (last = 0.1944), fitness=0.000122375\n",
      "157.99 secs, 9927 evals, 9697 steps, improv/step: 0.164 (last = 0.1053), fitness=0.000122375\n",
      "158.50 secs, 9966 evals, 9736 steps, improv/step: 0.163 (last = 0.1282), fitness=0.000122375\n",
      "159.01 secs, 9997 evals, 9767 steps, improv/step: 0.163 (last = 0.0000), fitness=0.000122375\n",
      "159.52 secs, 10030 evals, 9800 steps, improv/step: 0.163 (last = 0.1212), fitness=0.000122375\n",
      "160.02 secs, 10066 evals, 9836 steps, improv/step: 0.163 (last = 0.1111), fitness=0.000122375\n",
      "160.54 secs, 10092 evals, 9862 steps, improv/step: 0.162 (last = 0.1154), fitness=0.000122375\n",
      "161.05 secs, 10130 evals, 9900 steps, improv/step: 0.162 (last = 0.0526), fitness=0.000122375\n",
      "161.55 secs, 10168 evals, 9938 steps, improv/step: 0.162 (last = 0.1842), fitness=0.000122375\n",
      "162.06 secs, 10196 evals, 9967 steps, improv/step: 0.162 (last = 0.1034), fitness=0.000122375\n",
      "162.57 secs, 10222 evals, 9994 steps, improv/step: 0.162 (last = 0.2222), fitness=0.000122375\n",
      "\n",
      "Optimization stopped after 10001 steps and 162.68 seconds\n",
      "Termination reason: Max number of steps (10000) reached\n",
      "Steps per second = 61.48\n",
      "Function evals per second = 62.88\n",
      "Improvements/step = 0.16200\n",
      "Total function evaluations = 10229\n",
      "\n",
      "\n",
      "Best candidate found: [0.300088, 0.884932, 1.91793, 2.00462, 0.176313, 0.149841]\n",
      "\n",
      "Fitness: 0.000122375\n",
      "\n"
     ]
    },
    {
     "data": {
      "text/plain": [
       "BlackBoxOptim.OptimizationResults(\"adaptive_de_rand_1_bin_radiuslimited\", \"Max number of steps (10000) reached\", 10001, 1.575553392093e9, 162.67700004577637, DictChain{Symbol,Any}[DictChain{Symbol,Any}[Dict{Symbol,Any}(:RngSeed => 123340,:SearchRange => Tuple{Float64,Float64}[(0.1, 1.0), (0.1, 1.0), (1.5, 4.0), (1.5, 4.0), (0.05, 0.75), (0.1, 0.25)],:MaxSteps => 10000),Dict{Symbol,Any}()],Dict{Symbol,Any}(:FitnessScheme => ScalarFitnessScheme{true}(),:NumDimensions => :NotSpecified,:PopulationSize => 50,:MaxTime => 0.0,:SearchRange => (-1.0, 1.0),:Method => :adaptive_de_rand_1_bin_radiuslimited,:MaxNumStepsWithoutFuncEvals => 100,:RngSeed => 1234,:MaxFuncEvals => 0,:SaveTrace => false…)], 10229, ScalarFitnessScheme{true}(), BlackBoxOptim.TopListArchiveOutput{Float64,Array{Float64,1}}(0.00012237477101998878, [0.3000879389994999, 0.8849316302413965, 1.9179287750262926, 2.004615109299689, 0.17631265498980495, 0.1498405834595154]), BlackBoxOptim.PopulationOptimizerOutput{FitPopulation{Float64}}(FitPopulation{Float64}([0.3000339416835903 0.30002906647951005 … 0.2998911551028697 0.29993991763311506; 0.8922196662948053 0.892058510286837 … 0.8792749212423211 0.9067223651925492; … ; 0.17357198071564747 0.1735773935440087 … 0.17616051098854635 0.16677236943590248; 0.1498452100777135 0.1498487501217811 … 0.15007343547042828 0.14996824795976602], NaN, [0.00013668261211567258, 0.0001397860339672444, 0.00013978409750330055, 0.00013794714212117396, 0.00013837269489241295, 0.00013026523021544224, 0.00015024741189376663, 0.00014023719543146805, 0.00024001981648822394, 0.0001505572161084212  …  0.00015395474293318495, 0.0002611751051952438, 0.00028411895403892607, 0.00012237477101998878, 0.00019254334049529883, 0.0002435448823413269, 0.0001684680937268337, 0.00013977438931719004, 0.0001468655452705475, 0.00013480596161303247], 0, BlackBoxOptim.Candidate{Float64}[BlackBoxOptim.Candidate{Float64}([0.29880480596327286, 0.8445267976742463, 1.9085755976959176, 1.9660824530997343, 0.17792437613166018, 0.15151718954482588], 31, 0.0012551877485361925, BlackBoxOptim.AdaptiveDiffEvoRandBin{3}(BlackBoxOptim.AdaptiveDiffEvoParameters(BlackBoxOptim.BimodalCauchy(Distributions.Cauchy{Float64}(μ=0.65, σ=0.1), Distributions.Cauchy{Float64}(μ=1.0, σ=0.1), 0.5, false, true), BlackBoxOptim.BimodalCauchy(Distributions.Cauchy{Float64}(μ=0.1, σ=0.1), Distributions.Cauchy{Float64}(μ=0.95, σ=0.1), 0.5, false, true), [0.6261902343049117, 0.843430030324217, 0.7368513966736043, 0.8053251663742037, 0.6132221847594711, 0.6590810072492729, 0.43675730564325244, 1.0, 0.5743413379301606, 0.9435882694146726  …  0.6697714717834575, 0.624161774094745, 0.8398865119913571, 0.014342104655024612, 0.8968615241746991, 0.6035776095780596, 0.7411122520255475, 0.9443708040449552, 0.7921103003231158, 1.0], [0.9456811115754405, 0.16726356261367958, 0.9628749404102642, 0.43511585774242223, 1.0, 0.8057657192711437, 0.988182384005621, 0.17156821784655238, 0.03542870659005727, 0.2631305569807043  …  0.5215667253076903, 1.0, 0.9782741627907142, 0.9683382007890636, 1.0, 0.9524326061315721, 1.0, 0.9080279128169688, 1.0, 0.8845681560810993])), 0), BlackBoxOptim.Candidate{Float64}([0.3004005526728503, 0.8445267976742463, 1.8955480688572144, 2.0149419929072363, 0.1818384620967649, 0.14924960629525447], 31, 0.010686224053907168, BlackBoxOptim.AdaptiveDiffEvoRandBin{3}(BlackBoxOptim.AdaptiveDiffEvoParameters(BlackBoxOptim.BimodalCauchy(Distributions.Cauchy{Float64}(μ=0.65, σ=0.1), Distributions.Cauchy{Float64}(μ=1.0, σ=0.1), 0.5, false, true), BlackBoxOptim.BimodalCauchy(Distributions.Cauchy{Float64}(μ=0.1, σ=0.1), Distributions.Cauchy{Float64}(μ=0.95, σ=0.1), 0.5, false, true), [0.6261902343049117, 0.843430030324217, 0.7368513966736043, 0.8053251663742037, 0.6132221847594711, 0.6590810072492729, 0.43675730564325244, 1.0, 0.5743413379301606, 0.9435882694146726  …  0.6697714717834575, 0.624161774094745, 0.8398865119913571, 0.014342104655024612, 0.8968615241746991, 0.6035776095780596, 0.7411122520255475, 0.9443708040449552, 0.7921103003231158, 1.0], [0.9456811115754405, 0.16726356261367958, 0.9628749404102642, 0.43511585774242223, 1.0, 0.8057657192711437, 0.988182384005621, 0.17156821784655238, 0.03542870659005727, 0.2631305569807043  …  0.5215667253076903, 1.0, 0.9782741627907142, 0.9683382007890636, 1.0, 0.9524326061315721, 1.0, 0.9080279128169688, 1.0, 0.8845681560810993])), 0)])))"
      ]
     },
     "execution_count": 59,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "x_init = [0.9, 0.8, 2.5, 2.5, 0.1, 0.1]\n",
    "x_lb = [0.1, 0.1, 1.5, 1.5, 0.05, 0.1]\n",
    "x_ub = [1.0, 1.0, 4.0, 4.0, core_flood.initial_water_saturation, 0.25]\n",
    "\n",
    "res = bboptimize(f, SearchRange = [(0.1, 1.0), (0.1, 1.0), (1.5, 4.0), (1.5, 4.0), \n",
    "        (0.05, core_flood.initial_water_saturation), (0.1, 0.25)])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 60,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": "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",
      "text/plain": [
       "Figure(PyObject <Figure size 640x480 with 1 Axes>)"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": "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",
      "text/plain": [
       "Figure(PyObject <Figure size 640x480 with 1 Axes>)"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "text/plain": [
       "8.03717989215052e-5"
      ]
     },
     "execution_count": 60,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "x_init = best_candidate(res)\n",
    "vis_error(x_init, exp_data1, core_props, fluids_ls, fluids_hs, rel_perms_hs, core_flood)\n",
    "error_calc(x_init, exp_data1, core_props, fluids_ls, fluids_hs, rel_perms_hs, core_flood)"
   ]
  }
 ],
 "metadata": {
  "kernelspec": {
   "display_name": "Julia 1.3.0",
   "language": "julia",
   "name": "julia-1.3"
  },
  "language_info": {
   "file_extension": ".jl",
   "mimetype": "application/julia",
   "name": "julia",
   "version": "1.3.0"
  }
 },
 "nbformat": 4,
 "nbformat_minor": 4
}
